Negative Stereotypical Evaluation from Male Increase Female’s Cyber Aggression Behaviors: The Intergroup Sensitivity Effect

Negative Stereotypical Evaluation from Male Increase Female’s Cyber Aggression Behaviors: The Intergroup Sensitivity Effect | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Negative Stereotypical Evaluation from Male Increase Female’s Cyber Aggression Behaviors: The Intergroup Sensitivity Effect Yating Yang, Jingjing Song This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6602178/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background The intergroup sensitivity effect refers to the negative evaluation come from outgroup members will induce more negative emotions and aggression behaviors compared with the negative evaluation come from ingroup members. This study aimed to focus on female group, explored the intergroup sensitivity effect in the internet situation, and further analyzed its mechanism. Methods In study 1, we manipulated the negative stereotypical evaluation source, and measured the cyber aggression behavior towards the evaluator. Study 2 explored the influence mechanism of the intergroup sensitivity effect. We measured the participants’ negative emotion, discrimination perception and gender system justice. Results The results showed that the negative stereotypical evaluation from male induced female more cyber aggression towards the evaluator than that from female, negative emotion and discrimination perception played a mediation role in this relationship, and these mediation effects were only significant for the female individual with high gender system justice. Conclusion In summary, negative emotion, discrimination perception, and gender system justice could partly explain the internal mechanism of the intergroup sensitivity effect. intergroup sensitivity effect gender role discrimination perception cyber aggression Figures Figure 1 Introduction Previous studies have pointed out that the negative evaluation source would affect people's attitude, emotion, and aggressive behavior. Compared with the negative evaluation from ingroup, negative evaluation from the outgroup will make individual experience higher negative emotion, and induce more aggressive behavior, this phenomenon was named as intergroup sensitivity effect (Hornsey & Esposo, 2009). Intergroup sensitivity effect has been demonstrated in multiple groups, for example, country (Adelman & Dasgupta, 2019), religion (Ariyanto et al., 2010), and gender (Hoog, 2013). In current study, we intended to focus on the female group, and verified the intergroup sensitivity effect in the internet situation, furthermore paid attention to its internal mechanism. It would be helpful to find effective measures to alleviate the intergroup contradiction and gender-antagonism in internet. 1.1 Intergroup Sensitivity Effect Intergroup sensitivity effect refers to the negative evaluation from outgroup would induce more negative emotion and aggressive behavior than that from ingroup. Negative evaluations from outgroup member are more likely to be perceived as hostile and competitive motivation (Hornsey & Sarah, 2010; Thai et al., 2019 ), make people experience high self-threat sense (Hoog, 2013 ), thus, they have high possibility to take defensive countermeasures (Adelman & Dasgupta, 2019; Hoog, 2013 ), demean and attack the outgroup evaluator in order to maintain the positive ingroup identity (Elder et al., 2005 ). Whereas, negative evaluations from ingroup are more likely to be perceived as constructive motivation which is good for long-term ingroup interests, make people experience low self-threat sense, promote positive self-reflection within ingroup. Therefore, people have more possibility to be persuaded, and accept this negative evaluation (Adelman & Dasgupta, 2019). Social identity theory points out that group identity is an important factor influencing individual self-recognition and self-evaluation (Brewer & Gardner,1996). The negative evaluations from outgroup threaten individual’s positive ingroup identity (Adelman & Dasgupta, 2019), increase self-threat sense, and thus people attack the evaluator to protect their damaged self-esteem (Hoog, 2013 ). Social norm theory indicates (Sutton et al., 2006 ) that criticism from outgroup does not conform to the social norms of interpersonal communication, and is regarded as hostile and unfriend. The perception of violating social norms leads people dislike negative evaluations from outgroup members (Sutton et al., 2006 ). Previous studies have explored "what kind of negative evaluation" is more likely to induce intergroup sensitivity effect. The results indicated that concrete language expression (Moscatelli et al., 2019 ), and attached praise to the criticism (Hornsey et al., 2008 ) would decrease people's defense and resistance to negative evaluation. Therefore, the content of negative evaluation would affect the intergroup sensitive effect. Stereotype include positive and negative components, and negative stereotypical evaluation is a kind of negative evaluation based on group stereotype (Prentice & Carranza, 2002 ). We intent to analyze whether negative stereotypical evaluation would also induce intergroup sensitivity effect. The internet has become an important place for people to socialize, entertain and work (Zhou, 2018 ). Therefore, this study intent to verified the intergroup sensitivity effect in the internet situation. With a focus on female group, we speculated that negative stereotypical evaluation from male would induce female more cyber aggression toward the male evaluators than those from ingroup. 1.2 The mediators in the relationship between negative stereotypical evaluation source and cyber aggression It is necessary to pay attention to the influence path of negative stereotypical evaluation source affect cyber aggression. We speculated that negative emotion paly a mediation role in the relationship between negative stereotypical evaluation source and cyber aggression behavior. First, it has been demonstrated that negative stereotypical evaluation from outgroup induces angrier and madder than that from ingroup (Lv et al., 2017 ; Song et al., 2020 ), as it is more likely to be perceived as hostile and biased (Hoog, 2013 ). In addition, negative emotions narrow instantaneous thought-behavior range, and prompt quick decisions making. Each kind of negative emotion corresponds to a specific behavioral tendency, anger and mad induce aggressive behaviors (Chen et al., 2020 ; Li & Xu, 2019 ). Furthermore, previous studies have confirmed that emotion plays a mediating role in the relationship between negative stereotypical evaluation source and ingroup positive behaviors (Kulich et al., 2015 ; Song et al., 2021 ). Discrimination perception refers to individuals feel they are excluded and isolated by others. Compared with adults and men, the elderly and women, who have relatively low social status, are more easily have high discrimination perception (Schmitt et al., 2014 ). We speculated that discrimination perception may play a mediating role in the relationship between negative stereotypical evaluation source and cyber aggression behavior. First, previous studies have proved that negative stereotypical evaluation from outgroup is more likely to be perceived as intergroup prejudice and discrimination, and make individuals have high discrimination perception (Hornsey & Esposo, 2009). Whereas, negative stereotypical evaluation from ingroup is perceived as positive ingroup self-reflection which is conducive to ingroup-development and self-improvement (Hornsey & Esposo, 2009). In addition, discrimination perception would bring a series of negative effects. In order to maintain the positive group identity, increase self-esteem, people would attack and belittle the evaluators. Long-term discrimination perception would induce people's persistent problem behaviors, such as, smoking and drinking. It has been demonstrated in African American, Latino and Asian immigrant children (Deng et al., 2010 ). 1.3 The moderating role of gender system justice Researcher also have pay attention to the condition of intergroup sensitivity effect. Research has confirmed that for individuals with high group identity, negative evaluation from outgroup will bring greater negative impact (Song et al., 2021 ). Moreover, previous research indicated that when have audience (Hornsey et al., 2005 ), obvious intergroup conflict (Ariyanto et al., 2010 ), and critical attribution (Rabinovich & Morton, 2010 ) would increase people's defense and resistance to negative evaluation. We speculated that gender system justice may play a moderating role in the relationship between negative stereotypical evaluation source and cyber aggression. The gender system justice refers to people's subjective evaluation of whether the gender system and gender concept in current society are fair and reasonable. According to the systematic justice theory (Jost & Kay, 2005 ), both the dominant group and the subordinate group have a tendency to identify with the current social system (Martini & Piccoli, 2020 ). For the female with high gender system justice, they identify and support with the social role orientation of female, and deem the social gender system is fair, legal and reasonable (Kay et al., 2005 ), have a high gender ingroup identification, and might be have high degree of self-stereotyping to conform the gender role demand. The moderating role of gender system justice might exist two possible results. High gender system justice might lead to women can’t accept others' vilification towards women, especially from the outgroup, thus, intergroup sensitivity effect increases. They might have high possibility to perceive the negative stereotypical evaluation from outgroup as intergroup discrimination and intergroup bias compared with that from ingroup, damage the positive group self-identity, threaten the positive self-image, and induce more cyber aggression behavior. However, there might be another possibility that high gender system justice might lead to women perceive negative stereotypes evaluation as "correct", self-threat sense decrease, and thus, there might be none difference in emotion and aggression response brought by negative stereotypical evaluation from outgroup and ingroup. 1.4 Current study Based on the reviewed above, this study focused on female groups, explored the influence of negative stereotypical evaluation source on cyber aggression behavior, and further analyzed the mediating role of negative emotion and discrimination perception, as well as the moderating role of gender system justice. We hypothesized that: (1) For female participants, negative stereotypical evaluation from male would lead to more cyber aggression towards evaluators than that from female. (2) Negative stereotypical evaluation from male will induce more negative emotion and discrimination perception, and further lead to more cyber aggression. (3) The mediating effect only exists in the female with high or low gender system justice. Two experimental studies were conducted. Study 1 focused on the influence of negative stereotypical evaluation sources on cyber aggression behavior. In Study 2, the internal mechanism of the intergroup sensitivity effect was explored by measuring negative emotion, discrimination perception, and gender system justice. Study 1 The influence of negative stereotypical evaluation source on cyber aggression Study 1 intended to pay attention to whether negative stereotypical evaluation source influence cyber aggression behavior. We assumed that, for the female participants, negative stereotypical evaluation from male was less likeable, and led to more cyber aggression behavior compared with that from female. 2.1 Method 2.1.1 Participants A total of 124 female college students in central China voluntarily enrolled in research, after eliminating incomplete questionnaires, 108 valid data were collected, with age ranged from 17 to 28 years (M = 18.36, SD = 1.12). There were 70 (64.8%) participants come from rural and 38 (35.2%) participants from urban. Regard to participants’ subjective family economic situation, four participants (3.7%) were very poor, nine (8.3%) were a litter poor, 80 (74.1%) were medium, 14 (13.0%) were a litter rich, and one (0.9%) were very rich. 2.1.2 Experimental design and procedure We used the single factor between-subject design. The independent variable was the negative stereotypical evaluation source, and the dependent variable include likeability towards evaluator, their reaction to the negative evaluation, and cyber aggression towards evaluator. All procedures performed in studies involving human participants were in accordance with American Psychological Association (APA) standards, and the1964 Helsinki declaration and its later amendments or comparable ethical standards. Approval to conduct this study was obtained from the ethics committee of the Department of Psychology, China University of Geosciences (Wuhan). The participants took part in the research through online questionnaire. After filling in the informed consent form, the participants watched forum screenshot to manipulate the negative stereotypical evaluation source, and then they completed questionnaire. After completing the questionnaire, participants got a random red envelope as rewards. 2.1.3 Experimental materials Negative stereotypical evaluation source : referred to Hornsey & Sarah (2009), participants watched an online forum screenshot, in which someone asked "what major is suitable for female in the college.” A female or male answered this question with a negative stereotypical evaluation towards the female group. For the ingroup negative stereotypical evaluation condition, participants read the following response: "I am a woman. I think female are suitable for being full-time housewives, do housework, and take care of children. Regard to the career choose, female much more suitable for career like nurse and elementary school teacher." For the outgroup negative stereotypical evaluation condition, the participants read the same material except that the evaluator was male. The gender identity of evaluator can be presented through the language expression, profile picture and screen name. Manipulation check One item was used to test whether the participants noticed the gender of the evaluator, "Is the evaluator male or female?" The correct answer indicated that the participants aware of the gender identity of the evaluator. We deleted the data with incorrect answer. Response to negative stereotypical evaluation : A question was used to measure participants' response to the negative stereotypical evaluation, included three responses: like, dislike and no response. Likeability Two questions were used to measure likeability towards evaluators (Nicoleshelton et al., 2005 ). Participants answered these two items on a seven-point Likert scale (1 = completely inconsistent with my ideas, 7 = completely consistent with my ideas). This scale’s internal consistency was good in the current sample (Cronbach’s alpha = 0.92). Cyber aggression behavior Using a modified version of hot sauce distribution paradigm to measure cyber aggression behavior (Lieberman et al., 2010 ). We told the participants that “there is an online activity, you can assign some peppers to the evaluator, and evaluator should eat all the pepper they received. you can choose peppers from 0 to 100." The number of peppers assigned by the participants was index of aggressive behavior towards the evaluator. 2.2 Results Regard to the participants’ responses to negative stereotypical evaluation, when the negative evaluation come from ingroup, 1 participant “like”, 37 participants “dislike”, and 14 participants “no response”. When the negative evaluation come from outgroup, 2 participants “like”, 48 participants “dislike”, and 6 participants “no response”. Chi-square analysis results was significant, χ 2 = 4.9, p < 0.1. The results showed that the negative stereotypical evaluation come from outgroup have high possibility of getting “dislike” compared with that from ingroup. One-way variance analysis was used to explore the influence of negative stereotypical evaluation source on the likeability towards evaluator. The results were significant, F (1, 106) = 4.21, p < 0.05, η2 p = 0.04. People have high likeability towards the ingroup evaluator ( M = 5.61, SD = 2.64) than outgroup evaluator ( M = 5.61, SD = 2.64) who make negative stereotypical evaluation. One-way variance analysis was used to explore the influence of negative stereotypical evaluation source on the cyber aggression. The results were significant, F (1, 106) = 4.07, p < 0.05, η2 p = 0.04. People take more cyber aggression towards outgroup evaluator ( M = 60.41, SD = 40.87) compared with ingroup evaluator ( M = 44.58, SD = 40.62) who make negative stereotypical evaluation. The results of study 1 showed that for female participants, negative stereotypical evaluation from male were more disliked, and induced more aggression towards the evaluator, compared with that from female. This study verified the intergroup sensitivity effect in the internet situation. Study 2 The influence mechanism of negative stereotypical evaluation sources on cyber aggression Study 2 intended to investigate the mechanism of negative stereotypical evaluation source influencing cyber aggression, explored the mediating role of negative emotion and discrimination perception, and the moderating role of gender system justice. 3.1Methold 3.1.1 Participants We recruited 501 female college students in central China, after removing the invalid questionnaires and remaining 351 effective data. The participants’ age ranges from 17 to 24 (M = 18.16, SD = 0.73). There were 239 (68.1%) participants came from rural areas and 112 (31.9%) from urban areas. For their family economic situation, 8 (2.3%) participants were very poor, 49 (13.9%) were a litter poor, 278 (79.2%) were medium, 14 (4%) were a litter rich, 2 (0.6%) were very rich. 3.1.2 Procedure All procedures performed in studies involving human participants were in accordance with American Psychological Association (APA) standards, and the1964 Helsinki declaration and its later amendments or comparable ethical standards. Approval to conduct this study was obtained from the ethics committee of the Department of Psychology, China University of Geosciences (Wuhan). Participants completed the online questionnaire. After filling in the informed consent form, the participants watched a forum screenshot to manipulate the negative evaluation source, and then answered a series of questions. After completing all the questionnaire, participants got a random red envelope as rewards. 3.1.3 Experimental materials Negative stereotypical evaluation source Same as study 1. Negative emotion : The negative emotion scale (Nicoleshelton et al., 2005 ) was used to evaluate negative emotion, it included four kinds of emotion: Angry, sad, irritated, and insulted. Participants answered these four items from 0 to 100. The mean score of the four items represented the negative emotion. This scale’s internal consistency was good in the current sample (Cronbach’s alpha = 0.87). Discrimination perception Discrimination perception scale compiled by Shen et al. ( 2009 ) was used to measure participants’ discrimination perception. The questionnaire contained two dimensions and six items, three items examined individual discrimination perception and the other three items examined group discrimination perception. Participants answered these items on a five-point Likert scale (1 = completely inconsistent, 5 = completely consistent). The higher score indicated higher discrimination perception. This scale’s internal consistency was good in the current sample (Cronbach’s alpha = 0.87). Gender system justice The gender specific system justice questionnaire was used to measure the gender system justice (Jost & Kay, 2005 ), and it included 8 items. Participants answered these items on a seven-point Likert scale (1 = strongly disagree, 7 = strongly agree). The higher score indicated higher gender system justice belief. This scale’s internal consistency was acceptable in the current sample (Cronbach’s alpha = 0.47). Cyber aggression Same as Study 1. Manipulation check Same as Study 1. 3.2 Results 3.2.1 Descriptive statistics and correlations among variables The correlations among all variables were calculated using the Pearson’s product-moment correlation coefficient (see Table 1 ). The results indicated that the negative stereotyped evaluation source was positively correlated with negative emotion, discrimination perception and cyber aggression behavior. Cyber aggression behavior was positively correlated with the negative stereotypical evaluation source, negative emotion and discrimination perception. Thus, compared with the ingroup negative stereotypical evaluation, the outgroup negative stereotypical evaluation was significantly associated with more negative emotion, higher discrimination perception, and more cyber aggression. Table 1 Descriptive statistics and correlations result among all the variables Variable Evaluation source Negative emotion Discrimination perception Gender system justice Cyber aggression Evaluation source —— Negative emotion 0.12 * —— Discrimination perception 0.13 * 0.38 *** —— Gender system justice 0.06 0.06 -0.02 —— Cyber aggression 0.14 ** 0.41 *** 0.30 *** 0.07 —— M 1.50 36.42 18.89 39.83 49.14 SD 0.50 27.74 4.98 5.45 40.27 Note: Negative stereotypical evaluation source was dummy variables, mean for negative stereotypical evaluation source was the percentage of outgroup negative evaluation. *p < 0.05, **p < 0.01, ***p < 0.001. The single factor Harman test was used to assess the common method variance (Zhou & Long, 2004). The results of exploratory factor analysis showed that the first factor explained 24.86% of the variance (lower than the threshold of 40%), it indicated that the common method variance was not a serious threat to validity in current study. 3.2.3 The direct and indirect effect of negative stereotypical evaluation source on cyber aggression We used the PROCESS macro in SPSS (Hayes, 2018) to test the direct effect of negative stereotypical evaluation source on cyber aggression, and the indirect effect via negative emotion, discrimination perception, and gender system justice (see Fig. 1 ). As the moderator moderated the effect of independent variable on mediator and the effect of independent variable on dependent variable, we used Model 8 in the PROCESS. All predictors were standardized to minimize multicollinearity (Dearing & Hamilton, 2006). Moreover, the age, Hukou, and family economic situation were controlled in this model. Bootstrapping with 5000 iterations was used to generate an approximation of the sampling distribution in order to obtain accurate confidence intervals. In the model of independent and moderating variables affect negative emotions, after controlling demographic variables, negative stereotypical evaluation source was significantly positively associated with negative emotion ( β = 0.24, p < 0.05, LLCI = 0.0245, ULCL = 0.4476), gender system justice, interaction term of gender system justice and negative stereotypical evaluation source were not significantly associated with negative emotion ( β = -0.10, p = 0.55, LLCI = -0.4308, ULCL = 0.2309; β = 0.10, p = 0.35, LLCI = -0.1108, ULCL = 0.3130). In the model of independent and moderating variables affect discrimination perception, after controlling demographic variables, negative stereotypical evaluation source and gender system justice were both positively significantly associated with discrimination perception ( β = 0.27, p < 0.05, LLCI = 0.0651, ULCL = 0.4858; β = -0.33, p < 0.05, LLCI = -0.6587, ULCL = -0.0007), interaction term of gender system justice and negative stereotypical evaluation source was marginally significantly associated with discrimination perception ( β = 0.20, p = 0.058, LLCI = -0.0071, ULCL = 0.4144), see Table 2 . Table 2 ༎ The direct and indirect effect of negative stereotypical evaluation source on cyber aggression Dependent variable Independent variable β SE p 95%CI Negative emotion Evaluation source 0.24 0.11 0.03 [0.0245,0.4476] Gender system justice -0.10 0.17 0.55 -0.4308, 0.2309 Interaction term 0.10 0.11 0.35 -0.1108, 0.3130 Discrimination perception Evaluation source 0.27 0.11 0.01 [0.0651,0.4858] Gender system justice -0.33 0.17 0.05 -0.6587, -0.0007 Interaction term 0.20 0.11 0.06 -0.0071, 0.4144 Cyber aggression Evaluation source 0.16 0.10 0.10 [-0.0340,0.3543] Negative emotion 0.33 0.05 0.000 [0.2301,0.4370] Discrimination perception 0.16 0.05 0.002 [0.0597,0.2677] Gender system justice 0.14 0.15 0.34 -0.1563, 0.4471 Interaction term -0.06 0.10 0.51 -0.2575, 0.1289 Furthermore, in the model of independent, moderating variable, and mediating variable affect cyber aggression, after controlling demographic variables, negative stereotypical evaluation source was not significantly associated with cyber aggression ( β = 0.16, p = 0.10, LLCI = -0.0340, ULCL = 0.3543), negative emotion and discrimination perception were all significantly associated with cyber aggression ( β = 0.33, p < 0.001, LLCI = 0.2301, ULCL = 0.4370; β = 0.16, p < 0.01, LLCI = 0.0697, ULCL = 0.2677), gender system justice, and the interaction term of gender system justice and negative stereotypical evaluation source were not significantly associated with cyber aggression ( β = 0.14, p = 0.34, LLCI = -0.1563, ULCL = 0.4471; β = -0.06, p = 0.51, LLCI = -0.2575, ULCL = 0.1289). In order to clearly explain how the gender system justice moderated the relationship between negative stereotypical evaluation source and discrimination perception, simple slope test was conducted. The results showed that, for the individual with high gender system justice, negative stereotypical evaluation source was positively associated with discrimination perception ( β simple = 0.48, p < 0.01, LLCL = 0.1799, ULCL = 0.7782); for the individual with low gender system justice, negative stereotypical evaluation source was not significantly corelated with discrimination perception ( β simple = 0.07, p = 0.63, LLCL = -0.2246, ULCL = 0.3682). In order to clearly explain how the gender system justice moderated the mediation role of negative emotion in the relationship between the negative stereotypical evaluation source and cyber aggression, we made mediation model analysis for high and low gender system justice individual respectively. The results showed that, for the high gender system justice individual, the mediation role of negative emotion in the relationship between negative stereotypical evaluation source and cyber aggression was significant ( β = 0.11, LLCL = 0.0082, ULCL = 0.2304); for the individual with low gender system justice, the mediation role of negative emotion was not significant ( β = 0.04, LLCL = -0.0545, ULCL = 0.1594). In order to clearly explain how the gender system justice moderated the mediation role of discrimination perception in the relationship between the negative stereotypical evaluation source and cyber aggression, we made mediation model analysis for high and low gender system justice individual respectively. The results showed that, for the high gender system justice individual, the mediation role of discrimination perception in the relationship between negative stereotypical evaluation source and cyber aggression was significant ( β = 0.08, LLCL = 0.0151, ULCL = 0.1654); for the individual with low gender system justice, the mediation role of discrimination perception was not significant ( β = 0.01, LLCL = -0.0267, ULCL = 0.0582). Discussion This study focused on female, explored the influence of negative stereotypical evaluation source on cyber aggression, and its mechanism. First, previous studies have confirmed the intergroup sensitivity effect in country, religion, race, gender, university and other groups (Adelman & Dasgupta, 2019; Song et al., 2021 ). In current study, intergroup sensitivity effect was constructively and repeatedly verified in internet situation with negative stereotypical evaluations as independent variable and cyber aggression as dependent variable. Second, in current study, the modified version of hot sauce distribution paradigm was adopted to measure the cyber aggressive behavior. This measurement is consistent with the internet situation, and thus has high ecological validity. Moreover, this study explored the influence path and occurrence conditions of negative evaluation source affecting cyber aggression behavior, analyzed the mediating role of negative emotion and discrimination perception, and the moderating role of gender system justice. It could help us get a better understanding of the internal mechanism of intergroup sensitivity effect. We found that for female participants, negative stereotypical evaluation from male led to more cyber aggression toward the evaluator than those from female. The negative stereotypical evaluation from the in-group is easily to be perceived as well-intentioned, positive, and beneficial to the in-group development, and thus, it does not produce strong self-threat. The reason why women dislike the negative stereotypical evaluation from the outgroup might be that (1) the negative stereotypical evaluation from the outgroup is easily to be perceived as the stereotyped demands and oppressions towards women from men, which further makes the evaluators perceived it as hostile and biased, and offended (Hornsey & Sarah, 2010). (2) Negative evaluation towards female threatens women's positive group self and triggers women's defense mechanism. In order to defend their group identity, they derogate and demeans the out-group (Hornsey & Sarah, 2010). (3) Stereotyped evaluation also makes people think that the evaluator ignores individual uniqueness and simply perceive the evaluator as a group member. Therefore, women dislike men's negative stereotypical evaluation (Song et al., 2022). The mediating role of negative emotion in the relationship between negative evaluation source and cyber aggression behavior has been confirmed. Negative stereotypical evaluation from the outgroup lead to more anger, sadness, and insult than those from the ingroup (Song et al., 2021 ), which ultimately leads to more cyber aggression. This indicates that gender-based intergroup conflicts on network platforms are mostly driven by negative emotions. The mediating role of discrimination perception has also been confirmed. Women, as a vulnerable group in the gender, are more sensitive to gender discrimination (Schmitt et al., 2014 ). When negative evaluation come from outgroup, people tend to ignore individual uniqueness and attribute it to intergroup contradiction and intergroup conflict, perceived it as the demands and oppression on the female group from male, which demands women sacrifice themselves, serve the family, and obey the social authority. However, negative stereotypical evaluation towards female from their inner group may be perceived as women lowering their self-expectations to relieve perceived social pressure, or bending to social norms. Thus, women have more possibility to perceive outgroup’s negative evaluation as prejudice and discrimination than ingroup’s negative evaluation. The moderating effect of gender system justice belief on mediating effect was also confirmed. Only for women with high gender system justice, negative evaluation from the outgroup leads to more negative emotions and discrimination perception, and further leads to more cyber aggressive behavior. This may be because women with high gender system justice believe that the gender roles division in today's society is scientific and reasonable, have higher identification with the ingroup, female identity was important content of their self-concept. The negative stereotypical evaluation come from the outgroup would make them experience high self-identity threat, so it will induce more defense behaviors to protect one's self-esteem (Bagci et al., 2018 ). Whereas, for women with low gender system justice, they disagree with the current gender system, believe that gender inequality exists in today's society, disidentify with gender ingroup, and might be less self-stereotyping to compete current gender system and gender stereotype. The negative stereotypical evaluation come from the outgroup might make them think that "it is not me, I am not typical traditional woman", experience low self-threat sense, and thus, there are not significant difference in defense behavior between negative evaluation from the ingroup or outgroup. There are also some limitations in current study that are worthy of further research. First, this study only focuses on female groups. Future research is necessary to focus on male groups, to explore whether the intergroup sensitivity effect exist in the male group who are high socioeconomic status. The male may not perceive the negative stereotyped evaluation from the outgroup as discrimination and bias, or the male may arouse more negative reactions in the face of the negative evaluation from outgroup due to their high self-esteem. Secondly, future studies can further focus on the conditions that affect the intergroup sensitivity effect, what kind of people and what kind of negative evaluation content are more likely to induce intergroup sensitivity effect. Furthermore, current study focused on the mediating role of negative emotions. Future studies can refine negative emotions into anger, anxiety and sadness, and further analyze which negative emotions explain the relationship between the negative evaluation source and cyber aggression. Declarations Ethics approval and consent to participate All procedures performed in studies involving human participants were in accordance with American Psychological Association (APA) standards, and the1964 Helsinki declaration and its later amendments or comparable ethical standards. Approval to conduct the study was obtained from the ethics committee of institution of psychology, China university of geosciences (Wuhan). Informed consent was obtained from all study participants. Consent for publication Not applicable. Availability of data and material All data and materials are available upon request without participants' identifiable information. Competing interests The author declare that they have no conflict of interest. Funding We did not receive any funding from any source to conduct and complete the study. Authors' contributions JJS collected and analyzed the data, YTY completed the manuscript writing. Acknowledgements Not applicable. References Ariyanto, A., Hornsey, M. 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Exposure to benevolent sexism and complementary gender stereotypes: Consequences for specific and diffuse forms of system justification. Journal of Personality & Social Psychology, 88 (3),498–509. https://doi.org/10.2139/ssrn.386981 Kay, A. C., Jost, J. T., & Young, S. (2005). Victim derogation and victim enhancement as alternate routes to system justification. Psychological Science, 16 (3), 240–246. https://doi.org/ 10.2307/40064208 Kulich, C., Lorenzi-Cioldi, F., Iacoviello, V., Faniko, K., & Ryan, M. K. (2015). Signaling change during a crisis: Refining conditions for the glass cliff. Journal of Experimental Social Psychology, 61 , 96–103. https://doi.org/10.1016/j.jesp.2015.07.002 Lieberman, J. D., Solomon, S., Greenberg, J., & Mcgregor, H. A. (2010). A hot new way to measure aggression: Hot sauce allocation. Aggressive Behavior, 25 (5), 331–348. https://doi.org/10.1002/(SICI)1098-2337(1999)25:53.0.CO;2-1 Martini, M., & Piccoli, N. D. (2020). Predicting bystander intention to intervene: The role of gender-specific system justification and rape myth acceptance for men and women. Frontiers in Psychology, 11 , 326. https://doi.org/10.3389/fpsyg.2020.00326 Moscatelli, S., Prati, F., & Rubini, M. (2019). If you criticize us, do it in concrete terms: Linguistic abstraction as a moderator of the intergroup sensitivity effect. Journal of Language and Social Psychology, 38 (5), 680–705. https://doi.org/10.1177/0261927X19864686 Nicoleshelton, J., Richeson, J. A., Salvatore, J., & Trawalter, S. (2005). Ironic effects of racial bias during interracial interactions. Psychological Science, 16 (5), 397–402. https://doi.org/10.1111/j.0956-7976.2005.01547.x Prentice, D. A., & Carranza, E. (2002). What women and men should be, shouldn't be, are allowed to be, and don't have to be: The contents of prescriptive gender stereotypes. Psychology of Women Quarterly, 26 , 269–281. https://doi.org/10.1111/1471-6402.t01-1-00066 Rabinovich, A., & Morton, T. A. (2010). Who says we are bad people? The impact of criticism source and attributional content on responses to group-based criticism. Personality and Social Psychology Bulletin, 36 (4), 524–536. https://doi.org/10.1177/0146167210362980 Schmitt, M. T., Branscombe, N. R., Postmes, T., & Garcia, A. (2014). The consequences of perceived discrimination for psychological well-being: A meta-analytic review. Psychological Bulletin, 140 (4), 921–948. https://doi.org/10.1037/a0035754 Shen, J., Hu, X., & Liu, X. (2009). Left-over children’s perceived discrimination: its characteristics and relationship with personal well-being. Journal of Henan University (Social Science), (6), 116–121. Song, J., Li, J., Liu, Y., & Ruan, Y. (2021). The attitude of work-oriented and family-oriented Chinese women toward the evaluations based on the traditional positive stereotype that women are virtuous. Frontiers in Psychology,12 , 653234. https://doi.org/10.3389/fpsyg.2021.653234 Song, S., Zuo, B., Wen, F., & Tan, X. (2020). The intergroup sensitivity effect and its behavioral consequences: The influence of group identification. Acta Psychologica Sinica, 52 (8), 993-1003. Sutton, R. M., Elder, T. J., & Douglas, K. M. (2006). Reactions to internal and external criticism of outgroups: Social convention in the intergroup sensitivity effect. Personality and Social Psychology Bulletin, 32 (5), 563–575. https://doi.org/10.1177/0146167205282992 Thai, M., Borgella, A. M., & Sanchez, M. S. (2019). It's only funny if we say it: Disparagement humor is better received if it originates from a member of the group being disparaged. Journal of Experimental Social Psychology, 85 , 103838. https://doi.org/10.1016/j.jesp.2019.103838 Zhou, ZK. (2018). Cyber psychology . East China Normal University Press. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 13 Jun, 2025 Reviewers invited by journal 13 Jun, 2025 Editor invited by journal 21 May, 2025 Editor assigned by journal 16 May, 2025 Submission checks completed at journal 16 May, 2025 First submitted to journal 06 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6602178","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":471821017,"identity":"68a8abba-19cc-48be-8883-1410de03da20","order_by":0,"name":"Yating Yang","email":"","orcid":"","institution":"China University of Geosciences","correspondingAuthor":false,"prefix":"","firstName":"Yating","middleName":"","lastName":"Yang","suffix":""},{"id":471821018,"identity":"6ffcf5a6-accf-439e-8e30-a834186d8948","order_by":1,"name":"Jingjing Song","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYBACxmYoQ569sfFBQoUNCVoMew43Gzw4k0aKfTfS2yQfth0irJC5nffwyx8Vd+waGxLbKhLYDjDwt3cnEHAYX5o1z5lnye0MB9tuJPDcYZA4c3YDAS08ZsaMbYeTGRsbgVoknjEYSOQS1mL4E6iF4TBjW0GCwWGitBg/4G07bMdwjLGNISGBOC1mzDxnDicY9jA2SyQcSOMh6BfD/jPGH39UHLaXl3/+8OPPfzZy/O29BLQ0MLBJAOnEBqgAD17lICAPjJoPQNqeoMpRMApGwSgYuQAA+hFOhtUpx5gAAAAASUVORK5CYII=","orcid":"","institution":"China University of Geosciences","correspondingAuthor":true,"prefix":"","firstName":"Jingjing","middleName":"","lastName":"Song","suffix":""}],"badges":[],"createdAt":"2025-05-06 10:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6602178/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6602178/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84858742,"identity":"daaa5acd-0081-4a9e-b8a8-4e01580cdc79","added_by":"auto","created_at":"2025-06-18 06:37:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":90464,"visible":true,"origin":"","legend":"\u003cp\u003eThe direct and indirect effect of stereotypical evaluation source on cyber aggression\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6602178/v1/7b69cdf3da07161cab22cd5d.png"},{"id":84861255,"identity":"b77aa885-aecd-4aa7-8ee9-f48ad0e45431","added_by":"auto","created_at":"2025-06-18 07:01:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1148734,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6602178/v1/6d303cca-9b55-412a-a077-9a466e26221f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Negative Stereotypical Evaluation from Male Increase Female’s Cyber Aggression Behaviors: The Intergroup Sensitivity Effect","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePrevious studies have pointed out that the negative evaluation source would affect people\u0026apos;s attitude, emotion, and aggressive behavior. Compared with the negative evaluation from ingroup, negative evaluation from the outgroup will make individual experience higher negative emotion, and induce more aggressive behavior, this phenomenon was named as intergroup sensitivity effect (Hornsey \u0026amp; Esposo, 2009). Intergroup sensitivity effect has been demonstrated in multiple groups, for example, country (Adelman \u0026amp; Dasgupta, 2019), religion (Ariyanto et al., 2010), and gender (Hoog, 2013). In current study, we intended to focus on the female group, and verified the intergroup sensitivity effect in the internet situation, furthermore paid attention to its internal mechanism. It would be helpful to find effective measures to alleviate the intergroup contradiction and gender-antagonism in internet.\u003c/p\u003e\n\n\u003ch3\u003e1.1 Intergroup Sensitivity Effect\u003c/h3\u003e\n\u003cp\u003eIntergroup sensitivity effect refers to the negative evaluation from outgroup would induce more negative emotion and aggressive behavior than that from ingroup. Negative evaluations from outgroup member are more likely to be perceived as hostile and competitive motivation (Hornsey \u0026amp; Sarah, 2010; Thai et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), make people experience high self-threat sense (Hoog, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), thus, they have high possibility to take defensive countermeasures (Adelman \u0026amp; Dasgupta, 2019; Hoog, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), demean and attack the outgroup evaluator in order to maintain the positive ingroup identity (Elder et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Whereas, negative evaluations from ingroup are more likely to be perceived as constructive motivation which is good for long-term ingroup interests, make people experience low self-threat sense, promote positive self-reflection within ingroup. Therefore, people have more possibility to be persuaded, and accept this negative evaluation (Adelman \u0026amp; Dasgupta, 2019).\u003c/p\u003e \u003cp\u003eSocial identity theory points out that group identity is an important factor influencing individual self-recognition and self-evaluation (Brewer \u0026amp; Gardner,1996). The negative evaluations from outgroup threaten individual\u0026rsquo;s positive ingroup identity (Adelman \u0026amp; Dasgupta, 2019), increase self-threat sense, and thus people attack the evaluator to protect their damaged self-esteem (Hoog, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Social norm theory indicates (Sutton et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) that criticism from outgroup does not conform to the social norms of interpersonal communication, and is regarded as hostile and unfriend. The perception of violating social norms leads people dislike negative evaluations from outgroup members (Sutton et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrevious studies have explored \"what kind of negative evaluation\" is more likely to induce intergroup sensitivity effect. The results indicated that concrete language expression (Moscatelli et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and attached praise to the criticism (Hornsey et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) would decrease people's defense and resistance to negative evaluation. Therefore, the content of negative evaluation would affect the intergroup sensitive effect. Stereotype include positive and negative components, and negative stereotypical evaluation is a kind of negative evaluation based on group stereotype (Prentice \u0026amp; Carranza, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). We intent to analyze whether negative stereotypical evaluation would also induce intergroup sensitivity effect.\u003c/p\u003e \u003cp\u003eThe internet has become an important place for people to socialize, entertain and work (Zhou, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, this study intent to verified the intergroup sensitivity effect in the internet situation. With a focus on female group, we speculated that negative stereotypical evaluation from male would induce female more cyber aggression toward the male evaluators than those from ingroup.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.2 The mediators in the relationship between negative stereotypical evaluation source and cyber aggression\u003c/h2\u003e \u003cp\u003eIt is necessary to pay attention to the influence path of negative stereotypical evaluation source affect cyber aggression. We speculated that negative emotion paly a mediation role in the relationship between negative stereotypical evaluation source and cyber aggression behavior. First, it has been demonstrated that negative stereotypical evaluation from outgroup induces angrier and madder than that from ingroup (Lv et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), as it is more likely to be perceived as hostile and biased (Hoog, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In addition, negative emotions narrow instantaneous thought-behavior range, and prompt quick decisions making. Each kind of negative emotion corresponds to a specific behavioral tendency, anger and mad induce aggressive behaviors (Chen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li \u0026amp; Xu, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, previous studies have confirmed that emotion plays a mediating role in the relationship between negative stereotypical evaluation source and ingroup positive behaviors (Kulich et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDiscrimination perception refers to individuals feel they are excluded and isolated by others. Compared with adults and men, the elderly and women, who have relatively low social status, are more easily have high discrimination perception (Schmitt et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). We speculated that discrimination perception may play a mediating role in the relationship between negative stereotypical evaluation source and cyber aggression behavior. First, previous studies have proved that negative stereotypical evaluation from outgroup is more likely to be perceived as intergroup prejudice and discrimination, and make individuals have high discrimination perception (Hornsey \u0026amp; Esposo, 2009). Whereas, negative stereotypical evaluation from ingroup is perceived as positive ingroup self-reflection which is conducive to ingroup-development and self-improvement (Hornsey \u0026amp; Esposo, 2009). In addition, discrimination perception would bring a series of negative effects. In order to maintain the positive group identity, increase self-esteem, people would attack and belittle the evaluators. Long-term discrimination perception would induce people's persistent problem behaviors, such as, smoking and drinking. It has been demonstrated in African American, Latino and Asian immigrant children (Deng et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.3 The moderating role of gender system justice\u003c/h2\u003e \u003cp\u003eResearcher also have pay attention to the condition of intergroup sensitivity effect. Research has confirmed that for individuals with high group identity, negative evaluation from outgroup will bring greater negative impact (Song et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, previous research indicated that when have audience (Hornsey et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), obvious intergroup conflict (Ariyanto et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and critical attribution (Rabinovich \u0026amp; Morton, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) would increase people's defense and resistance to negative evaluation.\u003c/p\u003e \u003cp\u003eWe speculated that gender system justice may play a moderating role in the relationship between negative stereotypical evaluation source and cyber aggression. The gender system justice refers to people's subjective evaluation of whether the gender system and gender concept in current society are fair and reasonable. According to the systematic justice theory (Jost \u0026amp; Kay, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), both the dominant group and the subordinate group have a tendency to identify with the current social system (Martini \u0026amp; Piccoli, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For the female with high gender system justice, they identify and support with the social role orientation of female, and deem the social gender system is fair, legal and reasonable (Kay et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), have a high gender ingroup identification, and might be have high degree of self-stereotyping to conform the gender role demand.\u003c/p\u003e \u003cp\u003eThe moderating role of gender system justice might exist two possible results. High gender system justice might lead to women can\u0026rsquo;t accept others' vilification towards women, especially from the outgroup, thus, intergroup sensitivity effect increases. They might have high possibility to perceive the negative stereotypical evaluation from outgroup as intergroup discrimination and intergroup bias compared with that from ingroup, damage the positive group self-identity, threaten the positive self-image, and induce more cyber aggression behavior. However, there might be another possibility that high gender system justice might lead to women perceive negative stereotypes evaluation as \"correct\", self-threat sense decrease, and thus, there might be none difference in emotion and aggression response brought by negative stereotypical evaluation from outgroup and ingroup.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.4 Current study\u003c/h2\u003e \u003cp\u003e Based on the reviewed above, this study focused on female groups, explored the influence of negative stereotypical evaluation source on cyber aggression behavior, and further analyzed the mediating role of negative emotion and discrimination perception, as well as the moderating role of gender system justice. We hypothesized that: (1) For female participants, negative stereotypical evaluation from male would lead to more cyber aggression towards evaluators than that from female. (2) Negative stereotypical evaluation from male will induce more negative emotion and discrimination perception, and further lead to more cyber aggression. (3) The mediating effect only exists in the female with high or low gender system justice. Two experimental studies were conducted. Study 1 focused on the influence of negative stereotypical evaluation sources on cyber aggression behavior. In Study 2, the internal mechanism of the intergroup sensitivity effect was explored by measuring negative emotion, discrimination perception, and gender system justice.\u003c/p\u003e \u003c/div\u003e"},{"header":"Study 1 The influence of negative stereotypical evaluation source on cyber aggression","content":"\u003cp\u003eStudy 1 intended to pay attention to whether negative stereotypical evaluation source influence cyber aggression behavior. We assumed that, for the female participants, negative stereotypical evaluation from male was less likeable, and led to more cyber aggression behavior compared with that from female.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Method\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Participants\u003c/h2\u003e \u003cp\u003eA total of 124 female college students in central China voluntarily enrolled in research, after eliminating incomplete questionnaires, 108 valid data were collected, with age ranged from 17 to 28 years (M = 18.36, SD = 1.12). There were 70 (64.8%) participants come from rural and 38 (35.2%) participants from urban. Regard to participants’ subjective family economic situation, four participants (3.7%) were very poor, nine (8.3%) were a litter poor, 80 (74.1%) were medium, 14 (13.0%) were a litter rich, and one (0.9%) were very rich.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Experimental design and procedure\u003c/h2\u003e \u003cp\u003eWe used the single factor between-subject design. The independent variable was the negative stereotypical evaluation source, and the dependent variable include likeability towards evaluator, their reaction to the negative evaluation, and cyber aggression towards evaluator.\u003c/p\u003e \u003cp\u003e All procedures performed in studies involving human participants were in accordance with American Psychological Association (APA) standards, and the1964 Helsinki declaration and its later amendments or comparable ethical standards. Approval to conduct this study was obtained from the ethics committee of the Department of Psychology, China University of Geosciences (Wuhan). The participants took part in the research through online questionnaire. After filling in the informed consent form, the participants watched forum screenshot to manipulate the negative stereotypical evaluation source, and then they completed questionnaire. After completing the questionnaire, participants got a random red envelope as rewards.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3 Experimental materials\u003c/h2\u003e \u003cp\u003e \u003cb\u003eNegative stereotypical evaluation source\u003c/b\u003e: referred to Hornsey \u0026amp; Sarah (2009), participants watched an online forum screenshot, in which someone asked \"what major is suitable for female in the college.” A female or male answered this question with a negative stereotypical evaluation towards the female group. For the ingroup negative stereotypical evaluation condition, participants read the following response: \"I am a woman. I think female are suitable for being full-time housewives, do housework, and take care of children. Regard to the career choose, female much more suitable for career like nurse and elementary school teacher.\" For the outgroup negative stereotypical evaluation condition, the participants read the same material except that the evaluator was male. The gender identity of evaluator can be presented through the language expression, profile picture and screen name.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eManipulation check\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eOne item was used to test whether the participants noticed the gender of the evaluator, \"Is the evaluator male or female?\" The correct answer indicated that the participants aware of the gender identity of the evaluator. We deleted the data with incorrect answer.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eResponse to negative stereotypical evaluation\u003c/b\u003e: A question was used to measure participants' response to the negative stereotypical evaluation, included three responses: like, dislike and no response.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLikeability\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eTwo questions were used to measure likeability towards evaluators (Nicoleshelton et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Participants answered these two items on a seven-point Likert scale (1 = completely inconsistent with my ideas, 7 = completely consistent with my ideas). This scale’s internal consistency was good in the current sample (Cronbach’s alpha = 0.92).\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCyber aggression behavior\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eUsing a modified version of hot sauce distribution paradigm to measure cyber aggression behavior (Lieberman et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). We told the participants that “there is an online activity, you can assign some peppers to the evaluator, and evaluator should eat all the pepper they received. you can choose peppers from 0 to 100.\" The number of peppers assigned by the participants was index of aggressive behavior towards the evaluator.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Results\u003c/h2\u003e \u003cp\u003eRegard to the participants’ responses to negative stereotypical evaluation, when the negative evaluation come from ingroup, 1 participant “like”, 37 participants “dislike”, and 14 participants “no response”. When the negative evaluation come from outgroup, 2 participants “like”, 48 participants “dislike”, and 6 participants “no response”. Chi-square analysis results was significant, χ\u003csup\u003e2\u003c/sup\u003e = 4.9, p \u0026lt; 0.1. The results showed that the negative stereotypical evaluation come from outgroup have high possibility of getting “dislike” compared with that from ingroup.\u003c/p\u003e \u003cp\u003eOne-way variance analysis was used to explore the influence of negative stereotypical evaluation source on the likeability towards evaluator. The results were significant, \u003cem\u003eF\u003c/em\u003e (1, 106) = 4.21, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eη2 p\u003c/em\u003e = 0.04. People have high likeability towards the ingroup evaluator (\u003cem\u003eM\u003c/em\u003e = 5.61, \u003cem\u003eSD\u003c/em\u003e = 2.64) than outgroup evaluator (\u003cem\u003eM\u003c/em\u003e = 5.61, \u003cem\u003eSD\u003c/em\u003e = 2.64) who make negative stereotypical evaluation.\u003c/p\u003e \u003cp\u003eOne-way variance analysis was used to explore the influence of negative stereotypical evaluation source on the cyber aggression. The results were significant, \u003cem\u003eF\u003c/em\u003e (1, 106) = 4.07, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eη2 p\u003c/em\u003e = 0.04. People take more cyber aggression towards outgroup evaluator (\u003cem\u003eM\u003c/em\u003e = 60.41, \u003cem\u003eSD\u003c/em\u003e = 40.87) compared with ingroup evaluator (\u003cem\u003eM\u003c/em\u003e = 44.58, \u003cem\u003eSD\u003c/em\u003e = 40.62) who make negative stereotypical evaluation.\u003c/p\u003e \u003cp\u003eThe results of study 1 showed that for female participants, negative stereotypical evaluation from male were more disliked, and induced more aggression towards the evaluator, compared with that from female. This study verified the intergroup sensitivity effect in the internet situation.\u003c/p\u003e \u003c/div\u003e "},{"header":"Study 2 The influence mechanism of negative stereotypical evaluation sources on cyber aggression","content":"\u003cp\u003eStudy 2 intended to investigate the mechanism of negative stereotypical evaluation source influencing cyber aggression, explored the mediating role of negative emotion and discrimination perception, and the moderating role of gender system justice.\u003c/p\u003e\u003ch2\u003e3.1Methold\u003c/h2\u003e\u003ch2\u003e3.1.1 Participants\u003c/h2\u003e\u003cp\u003eWe recruited 501 female college students in central China, after removing the invalid questionnaires and remaining 351 effective data. The participants’ age ranges from 17 to 24 (M = 18.16, SD = 0.73). There were 239 (68.1%) participants came from rural areas and 112 (31.9%) from urban areas. For their family economic situation, 8 (2.3%) participants were very poor, 49 (13.9%) were a litter poor, 278 (79.2%) were medium, 14 (4%) were a litter rich, 2 (0.6%) were very rich.\u003c/p\u003e\u003ch2\u003e3.1.2 Procedure\u003c/h2\u003e\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with American Psychological Association (APA) standards, and the1964 Helsinki declaration and its later amendments or comparable ethical standards. Approval to conduct this study was obtained from the ethics committee of the Department of Psychology, China University of Geosciences (Wuhan). Participants completed the online questionnaire. After filling in the informed consent form, the participants watched a forum screenshot to manipulate the negative evaluation source, and then answered a series of questions. After completing all the questionnaire, participants got a random red envelope as rewards.\u003c/p\u003e\u003ch2\u003e3.1.3 Experimental materials\u003c/h2\u003e\u003cp\u003e \u003cstrong\u003eNegative stereotypical evaluation source\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eSame as study 1.\u003c/p\u003e\u003cp\u003e \u003cb\u003eNegative emotion\u003c/b\u003e: The negative emotion scale (Nicoleshelton et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) was used to evaluate negative emotion, it included four kinds of emotion: Angry, sad, irritated, and insulted. Participants answered these four items from 0 to 100. The mean score of the four items represented the negative emotion. This scale’s internal consistency was good in the current sample (Cronbach’s alpha = 0.87).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eDiscrimination perception\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eDiscrimination perception scale compiled by Shen et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) was used to measure participants’ discrimination perception. The questionnaire contained two dimensions and six items, three items examined individual discrimination perception and the other three items examined group discrimination perception. Participants answered these items on a five-point Likert scale (1 = completely inconsistent, 5 = completely consistent). The higher score indicated higher discrimination perception. This scale’s internal consistency was good in the current sample (Cronbach’s alpha = 0.87).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eGender system justice\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eThe gender specific system justice questionnaire was used to measure the gender system justice (Jost \u0026amp; Kay, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), and it included 8 items. Participants answered these items on a seven-point Likert scale (1 = strongly disagree, 7 = strongly agree). The higher score indicated higher gender system justice belief. This scale’s internal consistency was acceptable in the current sample (Cronbach’s alpha = 0.47).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eCyber aggression\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eSame as Study 1.\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eManipulation check\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eSame as Study 1.\u003c/p\u003e\u003ch2\u003e3.2 Results\u003c/h2\u003e\u003ch2\u003e3.2.1 Descriptive statistics and correlations among variables\u003c/h2\u003e\u003cp\u003eThe correlations among all variables were calculated using the Pearson’s product-moment correlation coefficient (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The results indicated that the negative stereotyped evaluation source was positively correlated with negative emotion, discrimination perception and cyber aggression behavior. Cyber aggression behavior was positively correlated with the negative stereotypical evaluation source, negative emotion and discrimination perception. Thus, compared with the ingroup negative stereotypical evaluation, the outgroup negative stereotypical evaluation was significantly associated with more negative emotion, higher discrimination perception, and more cyber aggression.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics and correlations result among all the variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvaluation source\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNegative emotion\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiscrimination perception\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGender system justice\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCyber aggression\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvaluation source\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e——\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative emotion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e——\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiscrimination perception\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e——\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender system justice\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e——\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCyber aggression\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.30\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e——\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.42\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.89\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.83\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.14\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.74\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.98\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.45\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.27\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Negative stereotypical evaluation source was dummy variables, mean for negative stereotypical evaluation source was the percentage of outgroup negative evaluation. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eThe single factor Harman test was used to assess the common method variance (Zhou \u0026amp; Long, 2004). The results of exploratory factor analysis showed that the first factor explained 24.86% of the variance (lower than the threshold of 40%), it indicated that the common method variance was not a serious threat to validity in current study.\u003c/p\u003e\u003cp\u003e\u0026lt;Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026gt;\u003c/p\u003e\u003ch2\u003e3.2.3 The direct and indirect effect of negative stereotypical evaluation source on cyber aggression\u003c/h2\u003e\u003cp\u003eWe used the PROCESS macro in SPSS (Hayes, 2018) to test the direct effect of negative stereotypical evaluation source on cyber aggression, and the indirect effect via negative emotion, discrimination perception, and gender system justice (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As the moderator moderated the effect of independent variable on mediator and the effect of independent variable on dependent variable, we used Model 8 in the PROCESS. All predictors were standardized to minimize multicollinearity (Dearing \u0026amp; Hamilton, 2006). Moreover, the age, Hukou, and family economic situation were controlled in this model. Bootstrapping with 5000 iterations was used to generate an approximation of the sampling distribution in order to obtain accurate confidence intervals.\u003c/p\u003e\u003cp\u003eIn the model of independent and moderating variables affect negative emotions, after controlling demographic variables, negative stereotypical evaluation source was significantly positively associated with negative emotion (\u003cem\u003eβ\u003c/em\u003e = 0.24, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eLLCI\u003c/em\u003e = 0.0245, \u003cem\u003eULCL\u003c/em\u003e = 0.4476), gender system justice, interaction term of gender system justice and negative stereotypical evaluation source were not significantly associated with negative emotion (\u003cem\u003eβ\u003c/em\u003e = -0.10, \u003cem\u003ep\u003c/em\u003e = 0.55, \u003cem\u003eLLCI\u003c/em\u003e = -0.4308, \u003cem\u003eULCL\u003c/em\u003e = 0.2309; \u003cem\u003eβ\u003c/em\u003e = 0.10, \u003cem\u003ep\u003c/em\u003e = 0.35, \u003cem\u003eLLCI\u003c/em\u003e = -0.1108, \u003cem\u003eULCL\u003c/em\u003e = 0.3130).\u003c/p\u003e\u003cp\u003eIn the model of independent and moderating variables affect discrimination perception, after controlling demographic variables, negative stereotypical evaluation source and gender system justice were both positively significantly associated with discrimination perception (\u003cem\u003eβ\u003c/em\u003e = 0.27, p \u0026lt; 0.05, LLCI = 0.0651, ULCL = 0.4858; \u003cem\u003eβ\u003c/em\u003e = -0.33, p \u0026lt; 0.05, LLCI = -0.6587, ULCL = -0.0007), interaction term of gender system justice and negative stereotypical evaluation source was marginally significantly associated with discrimination perception (\u003cem\u003eβ\u003c/em\u003e = 0.20, p = 0.058, LLCI = -0.0071, ULCL = 0.4144), see Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e༎ The direct and indirect effect of negative stereotypical evaluation source on cyber aggression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent\u003c/p\u003e \u003cp\u003evariable\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndependent\u003c/p\u003e \u003cp\u003evariable\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNegative emotion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvaluation source\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.0245,0.4476]\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender system justice\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.4308, 0.2309\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInteraction term\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.1108, 0.3130\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDiscrimination\u003c/p\u003e \u003cp\u003eperception\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvaluation source\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.0651,0.4858]\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender system justice\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.6587, -0.0007\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInteraction term\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.0071, 0.4144\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCyber\u003c/p\u003e \u003cp\u003eaggression\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvaluation source\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[-0.0340,0.3543]\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative emotion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.2301,0.4370]\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiscrimination perception\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.0597,0.2677]\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender system justice\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.1563, 0.4471\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInteraction term\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.2575, 0.1289\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eFurthermore, in the model of independent, moderating variable, and mediating variable affect cyber aggression, after controlling demographic variables, negative stereotypical evaluation source was not significantly associated with cyber aggression (\u003cem\u003eβ\u003c/em\u003e = 0.16, \u003cem\u003ep\u003c/em\u003e = 0.10, \u003cem\u003eLLCI\u003c/em\u003e = -0.0340, \u003cem\u003eULCL\u003c/em\u003e = 0.3543), negative emotion and discrimination perception were all significantly associated with cyber aggression (\u003cem\u003eβ\u003c/em\u003e = 0.33, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, \u003cem\u003eLLCI\u003c/em\u003e = 0.2301, \u003cem\u003eULCL\u003c/em\u003e = 0.4370; \u003cem\u003eβ\u003c/em\u003e = 0.16, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, \u003cem\u003eLLCI\u003c/em\u003e = 0.0697, \u003cem\u003eULCL\u003c/em\u003e = 0.2677), gender system justice, and the interaction term of gender system justice and negative stereotypical evaluation source were not significantly associated with cyber aggression (\u003cem\u003eβ\u003c/em\u003e = 0.14, \u003cem\u003ep\u003c/em\u003e = 0.34, \u003cem\u003eLLCI\u003c/em\u003e = -0.1563, \u003cem\u003eULCL\u003c/em\u003e = 0.4471; \u003cem\u003eβ\u003c/em\u003e = -0.06, \u003cem\u003ep\u003c/em\u003e = 0.51, \u003cem\u003eLLCI\u003c/em\u003e = -0.2575, \u003cem\u003eULCL\u003c/em\u003e = 0.1289).\u003c/p\u003e\u003cp\u003e\u0026lt;Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026gt;\u003c/p\u003e\u003cp\u003eIn order to clearly explain how the gender system justice moderated the relationship between negative stereotypical evaluation source and discrimination perception, simple slope test was conducted. The results showed that, for the individual with high gender system justice, negative stereotypical evaluation source was positively associated with discrimination perception (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003esimple\u003c/em\u003e\u003c/sub\u003e = 0.48, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, \u003cem\u003eLLCL\u003c/em\u003e = 0.1799, \u003cem\u003eULCL\u003c/em\u003e = 0.7782); for the individual with low gender system justice, negative stereotypical evaluation source was not significantly corelated with discrimination perception (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003esimple\u003c/em\u003e\u003c/sub\u003e = 0.07, \u003cem\u003ep\u003c/em\u003e = 0.63, \u003cem\u003eLLCL\u003c/em\u003e = -0.2246, \u003cem\u003eULCL\u003c/em\u003e = 0.3682).\u003c/p\u003e\u003cp\u003eIn order to clearly explain how the gender system justice moderated the mediation role of negative emotion in the relationship between the negative stereotypical evaluation source and cyber aggression, we made mediation model analysis for high and low gender system justice individual respectively. The results showed that, for the high gender system justice individual, the mediation role of negative emotion in the relationship between negative stereotypical evaluation source and cyber aggression was significant (\u003cem\u003eβ\u003c/em\u003e = 0.11, \u003cem\u003eLLCL\u003c/em\u003e = 0.0082, \u003cem\u003eULCL\u003c/em\u003e = 0.2304); for the individual with low gender system justice, the mediation role of negative emotion was not significant (\u003cem\u003eβ\u003c/em\u003e = 0.04, \u003cem\u003eLLCL\u003c/em\u003e = -0.0545, \u003cem\u003eULCL\u003c/em\u003e = 0.1594).\u003c/p\u003e\u003cp\u003eIn order to clearly explain how the gender system justice moderated the mediation role of discrimination perception in the relationship between the negative stereotypical evaluation source and cyber aggression, we made mediation model analysis for high and low gender system justice individual respectively. The results showed that, for the high gender system justice individual, the mediation role of discrimination perception in the relationship between negative stereotypical evaluation source and cyber aggression was significant (\u003cem\u003eβ\u003c/em\u003e = 0.08, \u003cem\u003eLLCL\u003c/em\u003e = 0.0151, \u003cem\u003eULCL\u003c/em\u003e = 0.1654); for the individual with low gender system justice, the mediation role of discrimination perception was not significant (\u003cem\u003eβ\u003c/em\u003e = 0.01, \u003cem\u003eLLCL\u003c/em\u003e = -0.0267, \u003cem\u003eULCL\u003c/em\u003e = 0.0582).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study focused on female, explored the influence of negative stereotypical evaluation source on cyber aggression, and its mechanism. First, previous studies have confirmed the intergroup sensitivity effect in country, religion, race, gender, university and other groups (Adelman \u0026amp; Dasgupta, 2019; Song et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In current study, intergroup sensitivity effect was constructively and repeatedly verified in internet situation with negative stereotypical evaluations as independent variable and cyber aggression as dependent variable. Second, in current study, the modified version of hot sauce distribution paradigm was adopted to measure the cyber aggressive behavior. This measurement is consistent with the internet situation, and thus has high ecological validity. Moreover, this study explored the influence path and occurrence conditions of negative evaluation source affecting cyber aggression behavior, analyzed the mediating role of negative emotion and discrimination perception, and the moderating role of gender system justice. It could help us get a better understanding of the internal mechanism of intergroup sensitivity effect.\u003c/p\u003e \u003cp\u003eWe found that for female participants, negative stereotypical evaluation from male led to more cyber aggression toward the evaluator than those from female. The negative stereotypical evaluation from the in-group is easily to be perceived as well-intentioned, positive, and beneficial to the in-group development, and thus, it does not produce strong self-threat. The reason why women dislike the negative stereotypical evaluation from the outgroup might be that (1) the negative stereotypical evaluation from the outgroup is easily to be perceived as the stereotyped demands and oppressions towards women from men, which further makes the evaluators perceived it as hostile and biased, and offended (Hornsey \u0026amp; Sarah, 2010). (2) Negative evaluation towards female threatens women's positive group self and triggers women's defense mechanism. In order to defend their group identity, they derogate and demeans the out-group (Hornsey \u0026amp; Sarah, 2010). (3) Stereotyped evaluation also makes people think that the evaluator ignores individual uniqueness and simply perceive the evaluator as a group member. Therefore, women dislike men's negative stereotypical evaluation (Song et al., 2022).\u003c/p\u003e \u003cp\u003eThe mediating role of negative emotion in the relationship between negative evaluation source and cyber aggression behavior has been confirmed. Negative stereotypical evaluation from the outgroup lead to more anger, sadness, and insult than those from the ingroup (Song et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which ultimately leads to more cyber aggression. This indicates that gender-based intergroup conflicts on network platforms are mostly driven by negative emotions.\u003c/p\u003e \u003cp\u003eThe mediating role of discrimination perception has also been confirmed. Women, as a vulnerable group in the gender, are more sensitive to gender discrimination (Schmitt et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). When negative evaluation come from outgroup, people tend to ignore individual uniqueness and attribute it to intergroup contradiction and intergroup conflict, perceived it as the demands and oppression on the female group from male, which demands women sacrifice themselves, serve the family, and obey the social authority. However, negative stereotypical evaluation towards female from their inner group may be perceived as women lowering their self-expectations to relieve perceived social pressure, or bending to social norms. Thus, women have more possibility to perceive outgroup\u0026rsquo;s negative evaluation as prejudice and discrimination than ingroup\u0026rsquo;s negative evaluation.\u003c/p\u003e \u003cp\u003eThe moderating effect of gender system justice belief on mediating effect was also confirmed. Only for women with high gender system justice, negative evaluation from the outgroup leads to more negative emotions and discrimination perception, and further leads to more cyber aggressive behavior. This may be because women with high gender system justice believe that the gender roles division in today's society is scientific and reasonable, have higher identification with the ingroup, female identity was important content of their self-concept. The negative stereotypical evaluation come from the outgroup would make them experience high self-identity threat, so it will induce more defense behaviors to protect one's self-esteem (Bagci et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Whereas, for women with low gender system justice, they disagree with the current gender system, believe that gender inequality exists in today's society, disidentify with gender ingroup, and might be less self-stereotyping to compete current gender system and gender stereotype. The negative stereotypical evaluation come from the outgroup might make them think that \"it is not me, I am not typical traditional woman\", experience low self-threat sense, and thus, there are not significant difference in defense behavior between negative evaluation from the ingroup or outgroup.\u003c/p\u003e \u003cp\u003eThere are also some limitations in current study that are worthy of further research. First, this study only focuses on female groups. Future research is necessary to focus on male groups, to explore whether the intergroup sensitivity effect exist in the male group who are high socioeconomic status. The male may not perceive the negative stereotyped evaluation from the outgroup as discrimination and bias, or the male may arouse more negative reactions in the face of the negative evaluation from outgroup due to their high self-esteem. Secondly, future studies can further focus on the conditions that affect the intergroup sensitivity effect, what kind of people and what kind of negative evaluation content are more likely to induce intergroup sensitivity effect. Furthermore, current study focused on the mediating role of negative emotions. Future studies can refine negative emotions into anger, anxiety and sadness, and further analyze which negative emotions explain the relationship between the negative evaluation source and cyber aggression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with American Psychological Association (APA) standards, and the1964 Helsinki declaration and its later amendments or comparable ethical standards. Approval to conduct the study was obtained from the ethics committee of institution of psychology, China university of geosciences (Wuhan). Informed consent was obtained from all study participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data and materials are available upon request without participants\u0026apos; identifiable information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe did not receive any funding from any source to conduct and complete the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJJS collected and analyzed the data, YTY completed the manuscript writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAriyanto, A., Hornsey, M. 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East China Normal University Press.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"intergroup sensitivity effect, gender role, discrimination perception, cyber aggression","lastPublishedDoi":"10.21203/rs.3.rs-6602178/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6602178/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe intergroup sensitivity effect refers to the negative evaluation come from outgroup members will induce more negative emotions and aggression behaviors compared with the negative evaluation come from ingroup members. This study aimed to focus on female group, explored the intergroup sensitivity effect in the internet situation, and further analyzed its mechanism.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn study 1, we manipulated the negative stereotypical evaluation source, and measured the cyber aggression behavior towards the evaluator. Study 2 explored the influence mechanism of the intergroup sensitivity effect. We measured the participants\u0026rsquo; negative emotion, discrimination perception and gender system justice.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results showed that the negative stereotypical evaluation from male induced female more cyber aggression towards the evaluator than that from female, negative emotion and discrimination perception played a mediation role in this relationship, and these mediation effects were only significant for the female individual with high gender system justice.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn summary, negative emotion, discrimination perception, and gender system justice could partly explain the internal mechanism of the intergroup sensitivity effect.\u003c/p\u003e","manuscriptTitle":"Negative Stereotypical Evaluation from Male Increase Female’s Cyber Aggression Behaviors: The Intergroup Sensitivity Effect","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 06:37:02","doi":"10.21203/rs.3.rs-6602178/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"238378663365123203210753132391873134871","date":"2025-06-13T14:45:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-13T12:56:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-21T06:59:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-16T08:10:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-16T08:06:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-05-06T10:42:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5da7a21e-07f5-4e74-9ba8-09c1255bf904","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-06-18T06:37:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-18 06:37:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6602178","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6602178","identity":"rs-6602178","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}