An examination of tweets posted before and after enactment of Twitter’s Suicide and Self-Harm Policy: a content analysis study.

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Elnaz Moghimi, Kevin Keller, Sanjeef Thampinathan, William Cipolli, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3933060/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The proliferation of suicide and self-harm content on social media platforms has emerged as a pressing concern in recent years, reflecting broader societal challenges surrounding mental health and online safety. In response to these concerns, platforms like Twitter (now “X”) have implemented policies aimed at curtailing the spread of such content and promoting user safety. The current study investigated the impact of Twitter's Suicide and Self-Harm Policy through a content analysis of tweets before and after its enactment, focusing on categorizing tweets according to slant, tweet category, and theme. A corpus of 3846 tweets was analyzed. Within this corpus, tweets spanning 32 weeks from October 18, 2018, to May 29, 2019, were selected. These dates were chosen to encompass approximately 16 weeks before and after the enactment of the policy on February 7, 2018. The analysis revealed notable shifts in the discourse surrounding self-harm, with discernible impacts attributed to the implementation of Twitter's policy. While the policy appeared to stimulate increased discussions aimed at fostering a better understanding of self-harm, it also underscored the necessity for social media platforms to delineate between factual information and personal opinions. However, the dissemination of personal accounts and experiences within these discussions served as a conduit for peer support, potentially offering invaluable assistance to individuals grappling with self-harm issues. Taken together, while policy interventions can stimulate constructive dialogue, careful consideration must be given to balancing factual accuracy with the provision of spaces for personal expression and support within online communities. Twitter Self-harm Suicide Social media content Content analysis Suicide and self-harm policy Tweet Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction According to the World Health Organization, more than 700,000 individuals die by suicide each year, making it the fourth leading cause of death amongst individuals aged 15 to 29 years [1]. Nonsuicidal self-injury (NSSI) has also become a prevalent global issue, with reported prevalence rates ranging from 4.86% to 16.9% [2, 3]. NSSI is defined as inflicting intentional harm towards oneself but without ending one’s life [4]. While there are many contributors associated with suicide and NSSI, social media is a predominant factor. Evidence suggests an association between social media use and self-injurious behaviors [5]. In a sample of 40,065 Norwegian university students from ages 18 to 35, those who actively used social media to post content had an increased risk of suicide and NSSI ideation [6]. Some reports attribute this risk to the contagion effect, where online social platforms facilitate the spread of thoughts, emotions, and behaviors across individuals and to the broader society [7]. Suicide and NSSI content can be spread and normalized via media exposure, ultimately leading to priming effects in vulnerable populations, including those without a history of these behaviors [8]. Accordingly, individuals active in online communities have reported learning about self-injury through these channels, and social learning has been linked to increases in suicide and NSSI [8, 9]. In a sample of individuals with recent episodes of NSSI, 43.6% reported learning about the behavior from peers or through media exposure [10]. Not surprisingly, social media platforms have been highly criticized for exposing users to harmful or provoking content, and a failure to provide safeguards that protect vulnerable populations Platforms like Twitter (now known as “X”) have offered a space for personal experiences and thoughts to be shared, including those pertaining to suicide and NSSI [11]. With more than 100 million users producing approximately 500 million tweets a day, content discussing suicide and NSSI is readily available [11]. A previous study categorized suicide and NSSI Twitter posts as manifestation of the behaviors, social responses to the behaviors, or exposure to the behaviors by mass communication [12]. Of these three responses, engagement in the behavior after exposure is the most concerning [13]. Meta-analytic data demonstrated that individuals who previously encountered suicide content were more than three times more likely to commit suicide and almost three times as likely to attempt suicide and survive [14]. Therefore, it is important to consider the precariousness of populating social media platforms with suicide and NSSI content. Social media applications like Twitter have been the primary engagement zones for digital self-harm content, particularly for young people [15]. Twitter's shared interest groups allows for anonymized communal conversations surrounding sensitive topics, creating an environment where users can be open without the fear of identification or judgment [16]. Currently, most major social media platforms have policies in place to regulate content related to suicide and NSSI. These platforms restrict explicit depictions of self-harm and/or they may add warning labels to graphic imagery. A significant policy development occurred on February 7, 2018, when Twitter enacted a Suicide and Self-harm Policy. Under the new guidelines, users who encouraged other users to engage in suicide, eating disorders, or any type of self-harm, though tweet or direct message, could have their post(s) removed and accounts temporarily locked or suspended [17]. The policy was established to mitigate self-harm behaviors by prohibiting their promotion or encouragement. The enactment of this policy provided a timely opportunity to explore patterns in the content posted during this time. Twitter’s ability to index public user posts according to specific words and phrases allows researchers to gather large sums of data and provide time-stamped monitoring of user posts. Therefore, the main objective of this study was to understand how the Suicide and Self-harm Policy impacted user posts related to suicide and NSSI. This approach aimed to shed light on whether the policy fulfills its objectives of filtering dangerous content. Research on the prevalence of suicide and NSSI content immediately before and after Twitter’s new policy is scant [18]. The findings of the current study highlight how policy contributes to social media content and shapes public dialogue. Methods 2.1 Twitter data The current study analyzed a subset of tweets that were utilized in a sentiment analysis and topic modelling study previously conducted by the authors [18]. Briefly, premium Twitter API [19] captured 238, 001 original posts, retweets, and quotes from June 1, 2018, to May 31, 2019, containing the terms “self-injurious behavior,” “nonsuicidal self-injury,” or “self-harm.” Tweets were included in the analysis if they were in English and were related to suicide or self-harm. Within this corpus, 32 weeks of tweets from October 18, 2018, to May 29, 2019, were selected. These dates were selected as they were approximately 16 weeks before and after the Suicide and Self-harm policy enacted on February 7, 2018 [20]. The rationale for selecting tweets within this range was to assess and compare the immediate impact of the policy on Twitter posts. Sample size was calculated using a priori power analysis via simulation (1000 iterations) for a Poisson regression model predicting the count of tweets per week by tweet type, opinion, and whether it was before or after the ban of graphic images of self-harm. We determined that a sample size of 84 tweets per week would yield adequate power (approximately 0.80) for detecting a small interactive effect. To account for the fact that many tweets do not have adequate information for coding (e.g., only links or emojis) and that some categories may be sparser than others, we took a random sample of 126 tweets per week (oversampled by 50%) for a total of 4,032 tweets. Given that the Twitter data is within the public domain and any identifying information was redacted from this observational study, an institutional ethical review of the protocol and informed consent were not deemed necessary. It is noted, however, that the initial analysis and data collection procedures in [18] were exempted by the Colgate University Institutional Review Board (IRB) according to the Code of Federal Regulations Title 45, Part 46 (Exemption 2: Public data). 2.2 Data analysis Tweets were aggregated and analyzed within an Excel file. Hashtags were not included in any of the analyses since the focus was on the content of the tweets rather than hashtags. Qualitative analysis of the tweets was conducted in two parts using content analysis methods [21, 22]. In the first part, individual tweets were organized into six categories that were adapted from a previous study evaluating tweets [23]: (1) Personal opinions; (2) Informative; (3) Jokes/Ridicule; (4) Personal Accounts/Experiences; (5) Advise-seeking; and (6) Other (for tweets that fell into none or more than one category). Individual tweets were also organized by pro, anti, or neutral slant when discussing suicide and/or self-harm. Two independent reviewers reviewed and coded the tweets, and inter-coder reliability was assessed via Cohen’s Kappa. Any discrepancies were resolved by a third reviewer. Manifest content analysis was used to explore the unique topics discussed within the tweet content [24]. This method provides an explicit, easily observable, and literal description of the phenomenon at hand by developing categories that stay close to the text [24, 25]. Initially, two independent coders analyzed approximately 2500 tweets to develop a codebook of coding categories. Each category represented shared meanings across the textual content of the tweets [26]. After discussion and revision amongst the research team, the codebook was applied to analyze the dataset. The final coding was reviewed by research team members, and any discrepancies were resolved through discussion. Lastly, descriptive statistics reported each tweet type’s mean, median, and standard deviations and slant from the two analyses. To compare trends before and after the enactment of the policy, tweet slants and types from before the ban (October 18, 2018, to February 6, 2019), were compared to those posted after the ban (February 8, 2019, to May 29, 2019). Results For the analysis, suicide and NSSI behaviors were collectively reported as self-harm. From the 4032 tweets, 186 were excluded (n = 143 not in English, n = 13 not relevant to self-harm, and n = 30 were on February 7th – the day the ban was announced). Subsequently, 3846 tweets were analyzed. Among these tweets, the level of agreement when coding was very high for type (Cohen’s k = 0.9294), slant (Cohen’s k = 0.9004), and the combined coding (Cohen’s k = 0.9018). Both before and after the enactment of the policy, the majority of tweets had an anti-self-harm slant and only 2.78% of the tweets were pro-self-harm. Most of the tweets were personal opinions (28.19%), followed by personal accounts and experiences (25.20%) and informative posts (24.41%). The most dominant themes included Understanding self-harm (41.11%), Political (16.56%), and Support (13.37%). While anti-self-harm tweets were less prevalent after the ban, neutral self-harm tweets were more prevalent (Fig. 1 ). Personal accounts and non-categorized tweets reduced after the ban (Fig. 2 ). Conversely, tweets that were personal opinions, informative, and advice-seeking became more prevalent (Fig. 2 ). The sole theme that became more prevalent after the ban was Understanding self-harm (Fig. 3 ). A full list of tweet slants, categories, and themes can be found in Table 1 . Table 1 Tweet counts, organized by date, slant, and type Total n(%) Pre-Ban Post-Ban ꭓ 2 (df), adjusted p Slant Anti 2611 (67.89) 1423 1188 50.4 (1), < 0.001 Neutral 1128 (29.33) 469 659 50.8 (1), < 0.001 Pro 107 (2.78) 52 55 0.002 (1), 0.756 Category Personal opinions 1084 (28.19) 464 620 35.8 (1), < 0.001 Informative 939 (24.42) 441 498 6.2 (1), 0.016 Jokes/ridicule 72 (1.87) 40 32 0.55 (1), 0.460 Personal account/experiences 969 (25.20) 592 377 57.1 (1), < 0.001 Advice-seeking 120 (3.12) 28 92 35.6 (1), < 0.001 Other 662 (17.21) 379 283 14.1 (1), < 0.001 Theme Accepting Self-Harm 6 (0.16) 5 1 1.4 (1), 0.2536 Calling Out Wrongdoings 488 (12.69) 355 133 109.2 (1), < 0.001 Comparisons 153 (3.98) 108 45 24.8 (1), <0.001 Feedback on Media Portrayal 133 (3.46) 75 58 1.6 (1), 0.2434 Political 637 (16.56) 400 237 45.2 (1), < 0.001 Reasons for Self-Harm 168 (4.37) 133 35 56.4 (1), < 0.001 Repercussions of Self-Harm 12 (0.31) 3 9 2.2 (1), 0.1896 Self-Harm Resources 106 (2.76) 80 26 26.1 (1), < 0.001 Self-Harm Terms 48 (1.25) 24 24 0 (1), 1 Support 514 (13.37) 298 216 12.8 (1), < 0.001 Understanding Self-Harm 1581 (41.11) 463 1118 484.0 (1), < 0.001 Theme summary Qualitative analysis of the tweets resulted in the emergence of ten themes (Table 2 ). Most of these tweets pertained to understanding self-harm (41.11%), political tweets that made self-harm inferences (16.56%), supporting individuals affected by self-harm (13.36%), and calling out wrongdoings (12.69%). Very few tweets promoted the acceptance of self-harm (0.31%). Table 2 Content analysis of tweets resulting in the emergence of 10 themes, organized in ascending order of frequency Theme Description Total # of tweets, n(%) Understanding self-harm Tools, research, and/or resources to better understand self-harm 1581 (41.11) Political Self-harm terms used in political information, commentary, or discussions 637 (16.56) Support Individual support given to or received by those affected by self-harm 514 (13.36) Calling out wrongdoings Discouraging or pointing out the negative implications associated with self-harm and/or its promotion 488 (12.69) Reasons for self-harm Specific factors that encourage engagement in self-harm 168 (4.36) Comparisons Self-harm was likened to lifestyle, objects, food, and certain behaviors 153 (3.98) Feedback on media portrayal Reflections on portrayals of self-harm in print and digital media 133 (3.46) Self-harm help resource Community services and resources for those affected by self-harm 106 (2.76) Minor themes Self-harm terms Single-word(s) posts that pertain to self-harm, without a coherent sentence structure 48 (1.25) Accepting self-harm Explicit promotion and/or glorification of self-harm behaviors 6 (0.31) Many tweets provided information to better understand what constitutes self-harm, who it may impact, and how it should be addressed. Most of these tweets were in discussion format (28%; 443/1581), where different users shared information on topics related to self-harm. Many tweets also supported raising awareness (19.9%; 314/1581) on self-harm. Information related to self-harm topics was also disseminated through links to news articles and blog posts (17.3%; 273/1581). Personal experiences of users were sometimes used to learn about self-harm (15.5%; 245/1581). Different reasons for engaging in self-harm were expressed by users. The most common reason was that the behavior was used as a coping mechanism (26.8%; 45/168). Urges or thoughts were also commonly expressed as a reason to self-harm (18.5%; 31/168). In some users, environmental factors, such as societal triggers and views on self-harm, also increased the risk of self-harm (8.9%; 15/168). The most common comparisons of self-harm were different lifestyle choices (26.1%; 40/153), such as staying up too late or travelling to certain regions. Consuming certain types of foods, particularly fast foods, was also seen as self-harm (13.1%; 20/153). Viewing certain TV shows and video games was also described as a form of self-harm (10.5%; 16/153). Much of the commentary about the media centered on self-harm portrayed in TV or film (39.1%; 52/133, social media (30.1%; 40/133), and books (14.3%; 19/133). Many of the tweets supported or challenged censorship of self-harm and highlighted the importance of discussing self-harm in these media formats. Many users expressed their opinions and thoughts on how self-harm information was portrayed and disseminated. The majority of these tweets focused on social media (15%; 73/488), with some users concerned about the lack of attention that social media companies pay to self-harm content and users reporting this content. Some users (13.9%; 68/488) also discussed the quality of care that made it difficult for individuals to seek help for self-harm. Other concerns that were expressed pertained to reducing bullying that may result in self-harm (12.7%; 62/488), trivializing or minimizing self-harm behaviors (9.8%; 48/488) and glorifying self-harm (7.8%; 38/488). Most political tweets considered certain policies and laws as being a form of self-harm. More than half of the political tweets centered on either the United Kingdom (18.1%; 115/637) or, more specifically, Brexit (51.2%; 326/637), referring to it as an act of self-harm. Many users indicated they were proud of themselves (39.7%; 204/514) and others (31.7%; 163/514) for coping with self-harm and their recovery journey. Several encouraging tweets mentioned the duration of time that individuals refrained from engaging in self-harm. Some users also expressed the need to get help from others (14%; 72/514). Links to resources for individuals seeking help from self-harm were predominantly treatments or services (34.9%; 37/106) or hotlines (35.8%; 38/106) provided by organizations focused on self-harm. Links to mobile applications to manage self-harm or related mental health concerns such as anxiety, panic attacks, and depression were also observed in the corpus of tweets (11.3%; 12/106). With respect to the minor themes, the majority of tweets accepting self-harm promoted the behavior and glorified self-harm as a positive activity that should be engaged in. Tweets pertaining to self-harm terms contained either a single word or multiple words related to self-harm and without a coherent sentence structure. Tweet slants and categories within themes With respect to tweet slants (Fig. 4 ), most of the anti-self-harm tweets (40.4%; 1055/2611) fell under the theme of Understanding self-harm . The same theme also had a large proportion of the total neutral slanted self-harm tweets (43.4%; 490/1128). While there were very few pro-self-harm tweets, most fell under the theme of Understanding self-harm (33.6%; 36/107) and Reasons for self-harm (29.9%; 32/107). Within almost all the themes, anti-self-harm tweets were the most predominant. Tweets categorized under Political (44.6%; 284/637), Comparisons (44.4%; 68/153), and Self-harm terms (81.3%; 39/48) were mostly neutral slanted. All themes under Accepting self-harm were pro-self harm tweets (n = 6). Conversely, none of the tweets that fell under the themes of Self-harm help resource (n = 106), Self-harm terms (n = 48), and Repercussions of self-harm (n = 12) contained pro-self-harm tweets. Regarding tweet categories (Fig. 5 ), most personal opinions fell under the theme of Understanding self-harm (38.5%; 417/1084) or Calling out wrongdoings (25.4%; 275/1084). More than half of informative tweets were also categorized as Understanding self-harm (77.6%; 729/939). Half of the tweets that were jokes or ridicule were Comparisons (50%; 36/72). Personal accounts and experiences were mostly coded under the themes of Support (35.2%; 341/969) or Understanding self-harm (32.5%; 315/969). Tweets under advice-seeking mostly represented the theme Understanding self-harm (46.7%; 56/120) or Support (29.2%; 35/120). Tweets that did not fall under any type were mostly Political (79.6%; 527/662). Discussion The current study aimed to develop an understanding of the types of tweets surrounding Twitter’s Suicide and Self-Harm policy. The findings indicated that the majority of tweets promoted a better understanding of self-harm, had an anti-self-harm slant, and were personal opinions. Personal opinions and informative tweets comprised the largest proportion of tweets intended to enhance understanding of self-harm. This finding highlights the importance of considering the types of information disseminated on the social media platform. Considering that a large proportion of social media users obtain their information online, the predominance of personal opinions may result in seemingly informative tweets being misleading or inaccurate. Indeed, the World Health Organization has recently coined the term Infodemic , characterized by an overwhelming influx of information, including false or misleading content in both digital and physical realms, leading to confusion and potentially harmful health-related behaviors [ 27 ]. Although infodemics have been defined in the context of disease outbreaks, their relevance to self-harm has been demonstrated in the current study. While the number of neutral tweets significantly increased after policy enactment, there was also a simultaneous increase in both informative tweets and personal opinions. Although the policy may have encouraged discourse surrounding a better understanding of self-harm, the information also has the potential to promote a skewed understanding of the topic. Future studies should consider how different types of tweets aimed at improving a user’s understanding of self-harm are perceived by users, particularly those vulnerable to suicide and NSSI. Despite concerns about how information is disseminated on Twitter, the high level of support expressed on the platform may provide insight into why many users may feel a sense of community and peer support [ 28 , 29 ]. The current study shed light on the dynamics of support - namely, that it provides a space for individuals to connect and support one another by sharing personal experiences with self-harm, providing resources to seek care, expressing specific reasons why self-harm may occur, and offering feedback on how these behaviors are portrayed in the media. While nearly all users called out the negative implications associated with self-harm, less than 1% posted pro-self-harm tweets that fell into this category. Many of these tweets accused social media of censoring their thoughts and opinions related to self-harm. In line with previous findings from the study authors and others, political tweets disseminated on the platform focused heavily on conflating Brexit with self-harm [ 18 , 30 ]. Nearly all of these tweets fell under none or more than one type and were either anti- or neutral-slanted. While the impact of calling social issues acts of self-harm has not been assessed, tweets that draw comparisons to self-harm may perpetuate mental health stigma [ 31 ]. It is critical for future work to determine if reporting Brexit in this manner may have contributed, at least to some degree, to the raised suicide risk in Brexit-voting communities [ 32 ] and increased anxiety and compromised mental health in migrants residing in the United Kingdom [ 33 ]. It certainly raises the intriguing linguistic finding of this study, where the term self-harm extended beyond traditional definitions of the behavior. A notable limitation of the study pertained to the self-harm language that was captured. Although the dissemination of self-harm content is a pervasive problem on social media, only about 3% of the total tweets analyzed were pro-self-harm. This number is substantially lower than reports of 9–66% pro-self-harm content within other social media platforms [ 34 ]. In contrast, a recent report indicated a 500% increase in self-harm-related hashtags since October 2022 [ 15 ]. The low number of pro-self-harm tweets in the current study may indicate that the ambiguous language of self-harm within social media platforms evolves in ways to bypass Suicide and Self-Harm policies [ 35 ]. A conspicuous example is that the same report highlighted an increased use of hashtags like “#shtwt,” which is short for S elf- H arm TW i T ter [ 15 ]. Given the dynamic and ever-changing nature of this language, it may be challenging to delineate unique terms and examples over the long term. However, future studies may benefit from outlining specific strategies and methods to identify less obvious terms and hashtags related to self-harm. Taken together, the current study demonstrated changes in the dialogue surrounding self-harm and how it may be impacted by policies targeted towards protecting users from exposure to potentially harmful content. While the policy may have increased conversations surrounding a better understanding of self-harm, it is important for social media platforms to clearly distinguish between what is factual and what is based on personal opinions. At the same time, personal opinions and the dissemination of personal accounts and experiences offer a space for peer support, which may benefit affected individuals. Declarations Author Contribution EM, HS, and WC were responsible for the study design. EM, KK, ST, and WC conducted data analysis. The main manuscript was written by EM, KK, and ST, and WC prepared all the study figures. All authors reviewed the manuscript. References World Health Organization (2023) Suicide. https://www.who.int/news-room/fact-sheets/detail/suicide Liu RT (2023) The epidemiology of non-suicidal self-injury: lifetime prevalence, sociodemographic and clinical correlates, and treatment use in a nationally representative sample of adults in England. 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Moghimi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYDACdhhDgrGBIaGCGC3MKFrOkKYFiBnbiNDBz8x78OMPhm1y8tHNrRsezrNO7GfvPfyZh8FOHpcWyWa+ZAkJhtvGhncOtt1I3JaeOLPnXJo0D0OyYQMOLQaHeQwkDBhuJ26ckQjScjhxw40cM2YehgOMuLTYH+Yx/pEA1zLncOL++2+MgQ47YI/TFmYeM4kDQC3zJUBaGoC2SPAYAB12IBGXFonDPGaWDQa3jQ1AWhKOpRvPOJNjJjnHIDkZlxb+9h7jmz8qbsvJz0h/dvNHjbVsf/sZ4w9vKuxscWmBOg+IDoBZzAgRgkC+AUXLKBgFo2AUjAIEAABzaVkXTKjwvgAAAABJRU5ErkJggg==","orcid":"","institution":"Waypoint Centre for Mental Health Care","correspondingAuthor":true,"prefix":"","firstName":"Elnaz","middleName":"","lastName":"Moghimi","suffix":""},{"id":272004088,"identity":"cf361fe0-dfc2-4bd8-92a0-cfb79f8928b3","order_by":1,"name":"Kevin Keller","email":"","orcid":"","institution":"University of South Carolina","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"","lastName":"Keller","suffix":""},{"id":272004089,"identity":"f0b48e9c-df56-4fe5-ae0a-932123e9dc04","order_by":2,"name":"Sanjeef Thampinathan","email":"","orcid":"","institution":"Queen's University","correspondingAuthor":false,"prefix":"","firstName":"Sanjeef","middleName":"","lastName":"Thampinathan","suffix":""},{"id":272004090,"identity":"bc151bd2-ed40-4a31-b884-0a024bc87122","order_by":3,"name":"William Cipolli","email":"","orcid":"","institution":"Colgate University","correspondingAuthor":false,"prefix":"","firstName":"William","middleName":"","lastName":"Cipolli","suffix":""},{"id":272004091,"identity":"e5e40fdb-033c-437b-85f6-7ade7e8248c5","order_by":4,"name":"Hayden Smith","email":"","orcid":"","institution":"University of South Carolina","correspondingAuthor":false,"prefix":"","firstName":"Hayden","middleName":"","lastName":"Smith","suffix":""}],"badges":[],"createdAt":"2024-02-06 06:49:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3933060/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3933060/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51018569,"identity":"aa792db9-4172-4bd9-9e2b-4100ccf14444","added_by":"auto","created_at":"2024-02-12 19:22:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":442995,"visible":true,"origin":"","legend":"\u003cp\u003eTweet slant before and after the ban on graphic images of self-harm (top) and contrasts in prevalence (bottom)\u003c/p\u003e","description":"","filename":"floatimage1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3933060/v1/2de667fcc6bda140739a9065.jpg"},{"id":51018571,"identity":"c8c5b240-e77d-4995-aad7-163056833f8f","added_by":"auto","created_at":"2024-02-12 19:22:27","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":584290,"visible":true,"origin":"","legend":"\u003cp\u003eTweet category before and after the ban on graphic images of self-harm (top) and contrasts in prevalence (bottom)\u003c/p\u003e","description":"","filename":"floatimage2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3933060/v1/1cb1d8c735eaf33c8932dae2.jpg"},{"id":51018572,"identity":"e49fc3b3-f876-4a73-ba05-8bd80ba4460d","added_by":"auto","created_at":"2024-02-12 19:22:27","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":771061,"visible":true,"origin":"","legend":"\u003cp\u003eTweet theme before and after the ban on graphic images of self-harm (top) and contrasts in prevalence (bottom)\u003c/p\u003e","description":"","filename":"floatimage3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3933060/v1/9125019f4473eb4f92f4e203.jpg"},{"id":51018570,"identity":"4a78eed3-f917-424a-831d-a180142833d9","added_by":"auto","created_at":"2024-02-12 19:22:27","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":458166,"visible":true,"origin":"","legend":"\u003cp\u003eTweet slant, organized by theme\u003c/p\u003e","description":"","filename":"floatimage4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3933060/v1/6a4caf1b5eecad8454b894de.jpg"},{"id":51018573,"identity":"0a7724bd-f183-422d-bc71-22584919b152","added_by":"auto","created_at":"2024-02-12 19:22:27","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":533664,"visible":true,"origin":"","legend":"\u003cp\u003eTweet category, organized by theme\u003c/p\u003e","description":"","filename":"floatimage5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3933060/v1/0131eff6726fd5ebf1f7458e.jpg"},{"id":51398522,"identity":"34fed6ce-dab6-4ab6-a9a2-28ba80fa2325","added_by":"auto","created_at":"2024-02-20 21:07:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":578648,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3933060/v1/bb30ca48-c04b-44c6-8786-80c120c3f76b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An examination of tweets posted before and after enactment of Twitter’s Suicide and Self-Harm Policy: a content analysis study.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the World Health Organization, more than 700,000 individuals die by suicide each year, making it the fourth leading cause of death amongst individuals aged 15 to 29 years [1]. \u0026nbsp;Nonsuicidal self-injury (NSSI) has also become a prevalent global issue, with reported prevalence rates ranging from 4.86% to 16.9% [2, 3]. NSSI is defined as inflicting intentional harm towards oneself but without ending one\u0026rsquo;s life [4]. While there are many contributors associated with suicide and NSSI, social media is a predominant factor.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEvidence suggests an association between social media use and self-injurious behaviors [5]. In a sample of 40,065 Norwegian university students from ages 18 to 35, those who actively used social media to post content had an increased risk of suicide and NSSI ideation [6]. Some reports attribute this risk to the contagion effect, where online social platforms facilitate the spread of thoughts, emotions, and behaviors across individuals and to the broader society [7]. Suicide and NSSI content can be spread and normalized via media exposure, ultimately leading to priming effects in vulnerable populations, including those without a history of these behaviors [8]. Accordingly, individuals active in online communities have reported learning about self-injury through these channels, and social learning has been linked to increases in suicide and NSSI [8, 9]. In a sample of individuals with recent episodes of NSSI, 43.6% reported learning about the behavior from peers or through media exposure [10]. Not surprisingly, social media platforms have been highly criticized for exposing users to harmful or provoking content, and a failure to provide safeguards that protect vulnerable populations\u003c/p\u003e\n\u003cp\u003ePlatforms like Twitter (now known as \u0026ldquo;X\u0026rdquo;) have offered a space for personal experiences and thoughts to be shared, including those pertaining to suicide and NSSI [11]. With more than 100 million users producing approximately 500 million tweets a day, content discussing suicide and NSSI is readily available [11]. A previous study categorized suicide and NSSI Twitter posts as \u0026nbsp;manifestation of the behaviors, social responses to the behaviors, or exposure to the behaviors by mass communication [12]. Of these three responses, engagement in the behavior after exposure is the most concerning [13]. Meta-analytic data demonstrated that individuals who previously encountered suicide content were more than three times more likely to commit suicide and almost three times as likely to attempt suicide and survive [14]. Therefore, it is important to consider the precariousness of populating social media platforms with suicide and NSSI content. Social media applications like Twitter have been the primary engagement zones for digital self-harm content, particularly for young people [15]. Twitter\u0026apos;s shared interest groups allows for anonymized communal conversations surrounding sensitive topics, creating an environment where users can be open without the fear of identification or judgment [16].\u003c/p\u003e\n\u003cp\u003eCurrently, most major social media platforms have policies in place to regulate content related to suicide and NSSI. These platforms restrict explicit depictions of self-harm and/or they may add warning labels to graphic imagery. A significant policy development occurred on February 7, 2018, when Twitter enacted a Suicide and Self-harm Policy. Under the new guidelines, users who encouraged other users to engage in suicide, eating disorders, or any type of self-harm, though tweet or direct message, could have their post(s) removed and accounts temporarily locked or suspended [17]. The policy was established to mitigate self-harm behaviors by prohibiting their promotion or encouragement. The enactment of this policy provided a timely opportunity to explore patterns in the content posted during this time. Twitter\u0026rsquo;s ability to index public user posts according to specific words and phrases allows researchers to gather large sums of data and provide time-stamped monitoring of user posts.\u003c/p\u003e\n\u003cp\u003eTherefore, the main objective of this study was to understand how the Suicide and Self-harm Policy impacted user posts related to suicide and NSSI. This approach aimed to shed light on whether the policy fulfills its objectives of filtering dangerous content. Research on the prevalence of suicide and NSSI content immediately before and after Twitter\u0026rsquo;s new policy is scant [18]. The findings of the current study highlight how policy contributes to social media content and shapes public dialogue.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Twitter data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current study analyzed a subset of tweets that were utilized in a sentiment analysis and topic modelling study previously conducted by the authors [18]. Briefly, premium Twitter API [19] captured 238, 001 original posts, retweets, and quotes from June 1, 2018, to May 31, 2019, containing the terms \u0026ldquo;self-injurious behavior,\u0026rdquo; \u0026ldquo;nonsuicidal self-injury,\u0026rdquo; or \u0026ldquo;self-harm.\u0026rdquo; Tweets were included in the analysis if they were in English and were related to suicide or self-harm.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWithin this corpus, 32 weeks of tweets from October 18, 2018, to May 29, 2019, were selected. These dates were selected as they were approximately 16 weeks before and after the Suicide and Self-harm policy enacted on February 7, 2018 [20]. The rationale for selecting tweets within this range was to assess and compare the immediate impact of the policy on Twitter posts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSample size was calculated using \u003cem\u003ea priori\u0026nbsp;\u003c/em\u003epower analysis via simulation (1000 iterations) for a Poisson regression model predicting the count of tweets per week by tweet type, opinion, and whether it was before or after the ban of graphic images of self-harm. We determined that a sample size of 84 tweets per week would yield adequate power (approximately 0.80) for detecting a small interactive effect. To account for the fact that many tweets do not have adequate information for coding (e.g., only links or emojis) and that some categories may be sparser than others, we took a random sample of 126 tweets per week (oversampled by 50%) for a total of 4,032 tweets.\u003c/p\u003e\n\u003cp\u003eGiven that the Twitter data is within the public domain and any identifying information was redacted from this observational study, an institutional ethical review of the protocol and informed consent were not deemed necessary. It is noted, however, that the initial analysis and data collection procedures in [18] were exempted by the Colgate University Institutional Review Board (IRB) according to the Code of Federal Regulations Title 45, Part 46 (Exemption 2: Public data).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTweets were aggregated and analyzed within an Excel file. Hashtags were not included in any of the analyses since the focus was on the content of the tweets rather than hashtags. Qualitative analysis of the tweets was conducted in two parts using content analysis methods [21, 22]. In the first part, individual tweets were organized into six categories that were adapted from a previous study evaluating tweets [23]: (1) Personal opinions; (2) Informative; (3) Jokes/Ridicule; (4) Personal Accounts/Experiences; (5) Advise-seeking; and (6) Other (for tweets that fell into none or more than one category). Individual tweets were also organized by pro, anti, or neutral slant when discussing suicide and/or self-harm. Two independent reviewers reviewed and coded the tweets, and inter-coder reliability was assessed via Cohen\u0026rsquo;s Kappa. Any discrepancies were resolved by a third reviewer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eManifest content analysis was used to explore the unique topics discussed within the tweet content [24]. This method provides an explicit, easily observable, and literal description of the phenomenon at hand by developing categories that stay close to the text [24, 25]. Initially, two independent coders analyzed approximately 2500 tweets to develop a codebook of coding categories. Each category represented shared meanings across the textual content of the tweets [26]. After discussion and revision amongst the research team, the codebook was applied to analyze the dataset. The final coding was reviewed by research team members, and any discrepancies were resolved through discussion.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLastly, descriptive statistics reported each tweet type\u0026rsquo;s mean, median, and standard deviations and slant from the two analyses. To compare trends before and after the enactment of the policy, tweet slants and types from before the ban (October 18, 2018, to February 6, 2019), were compared to those posted after the ban (February 8, 2019, to May 29, 2019).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFor the analysis, suicide and NSSI behaviors were collectively reported as self-harm. From the 4032 tweets, 186 were excluded (n\u0026thinsp;=\u0026thinsp;143 not in English, n\u0026thinsp;=\u0026thinsp;13 not relevant to self-harm, and n\u0026thinsp;=\u0026thinsp;30 were on February 7th \u0026ndash; the day the ban was announced). Subsequently, 3846 tweets were analyzed. Among these tweets, the level of agreement when coding was very high for type (Cohen\u0026rsquo;s k\u0026thinsp;=\u0026thinsp;0.9294), slant (Cohen\u0026rsquo;s k\u0026thinsp;=\u0026thinsp;0.9004), and the combined coding (Cohen\u0026rsquo;s k\u0026thinsp;=\u0026thinsp;0.9018).\u003c/p\u003e \u003cp\u003eBoth before and after the enactment of the policy, the majority of tweets had an anti-self-harm slant and only 2.78% of the tweets were pro-self-harm. Most of the tweets were personal opinions (28.19%), followed by personal accounts and experiences (25.20%) and informative posts (24.41%). The most dominant themes included \u003cem\u003eUnderstanding self-harm\u003c/em\u003e (41.11%), \u003cem\u003ePolitical\u003c/em\u003e (16.56%), and \u003cem\u003eSupport\u003c/em\u003e (13.37%). While anti-self-harm tweets were less prevalent after the ban, neutral self-harm tweets were more prevalent (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Personal accounts and non-categorized tweets reduced after the ban (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Conversely, tweets that were personal opinions, informative, and advice-seeking became more prevalent (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The sole theme that became more prevalent after the ban was \u003cem\u003eUnderstanding self-harm\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A full list of tweet slants, categories, and themes can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\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\u003eTweet counts, organized by date, slant, and type\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal n(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePre-Ban\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePost-Ban\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eꭓ\u003csup\u003e2\u003c/sup\u003e(df), adjusted p\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSlant\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnti\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2611 (67.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.4 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNeutral\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1128 (29.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.8 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePro\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107 (2.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002 (1), 0.756\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCategory\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePersonal opinions\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1084 (28.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.8 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eInformative\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e939 (24.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.2 (1), 0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eJokes/ridicule\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72 (1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55 (1), 0.460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePersonal account/experiences\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e969 (25.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.1 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAdvice-seeking\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120 (3.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.6 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e662 (17.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.1 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTheme\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAccepting Self-Harm\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.4 (1), 0.2536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCalling Out Wrongdoings\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e488 (12.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e109.2 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eComparisons\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e153 (3.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.8 (1), \u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFeedback on Media Portrayal\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e133 (3.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6 (1), 0.2434\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePolitical\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e637 (16.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.2 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eReasons for Self-Harm\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e168 (4.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.4 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRepercussions of Self-Harm\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2 (1), 0.1896\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSelf-Harm Resources\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e106 (2.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.1 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSelf-Harm Terms\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48 (1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (1), 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSupport\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e514 (13.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.8 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUnderstanding Self-Harm\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1581 (41.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e484.0 (1), \u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTheme summary\u003c/h3\u003e\n\u003cp\u003eQualitative analysis of the tweets resulted in the emergence of ten themes (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most of these tweets pertained to understanding self-harm (41.11%), political tweets that made self-harm inferences (16.56%), supporting individuals affected by self-harm (13.36%), and calling out wrongdoings (12.69%). Very few tweets promoted the acceptance of self-harm (0.31%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\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\u003eContent analysis of tweets resulting in the emergence of 10 themes, organized in ascending order of frequency\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTheme\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal # of tweets, n(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstanding self-harm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTools, research, and/or resources to better understand self-harm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1581 (41.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolitical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-harm terms used in political information, commentary, or discussions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e637 (16.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual support given to or received by those affected by self-harm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e514 (13.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalling out wrongdoings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiscouraging or pointing out the negative implications associated with self-harm and/or its promotion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e488 (12.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReasons for self-harm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecific factors that encourage engagement in self-harm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168 (4.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComparisons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-harm was likened to lifestyle, objects, food, and certain behaviors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153 (3.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeedback on media portrayal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReflections on portrayals of self-harm in print and digital media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e133 (3.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-harm help resource\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommunity services and resources for those affected by self-harm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (2.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMinor themes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-harm terms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle-word(s) posts that pertain to self-harm, without a coherent sentence structure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccepting self-harm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExplicit promotion and/or glorification of self-harm behaviors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMany tweets provided information to better understand what constitutes self-harm, who it may impact, and how it should be addressed. Most of these tweets were in discussion format (28%; 443/1581), where different users shared information on topics related to self-harm. Many tweets also supported raising awareness (19.9%; 314/1581) on self-harm. Information related to self-harm topics was also disseminated through links to news articles and blog posts (17.3%; 273/1581). Personal experiences of users were sometimes used to learn about self-harm (15.5%; 245/1581). Different reasons for engaging in self-harm were expressed by users. The most common reason was that the behavior was used as a coping mechanism (26.8%; 45/168). Urges or thoughts were also commonly expressed as a reason to self-harm (18.5%; 31/168). In some users, environmental factors, such as societal triggers and views on self-harm, also increased the risk of self-harm (8.9%; 15/168).\u003c/p\u003e \u003cp\u003eThe most common comparisons of self-harm were different lifestyle choices (26.1%; 40/153), such as staying up too late or travelling to certain regions. Consuming certain types of foods, particularly fast foods, was also seen as self-harm (13.1%; 20/153). Viewing certain TV shows and video games was also described as a form of self-harm (10.5%; 16/153). Much of the commentary about the media centered on self-harm portrayed in TV or film (39.1%; 52/133, social media (30.1%; 40/133), and books (14.3%; 19/133). Many of the tweets supported or challenged censorship of self-harm and highlighted the importance of discussing self-harm in these media formats. Many users expressed their opinions and thoughts on how self-harm information was portrayed and disseminated. The majority of these tweets focused on social media (15%; 73/488), with some users concerned about the lack of attention that social media companies pay to self-harm content and users reporting this content. Some users (13.9%; 68/488) also discussed the quality of care that made it difficult for individuals to seek help for self-harm. Other concerns that were expressed pertained to reducing bullying that may result in self-harm (12.7%; 62/488), trivializing or minimizing self-harm behaviors (9.8%; 48/488) and glorifying self-harm (7.8%; 38/488). Most political tweets considered certain policies and laws as being a form of self-harm. More than half of the political tweets centered on either the United Kingdom (18.1%; 115/637) or, more specifically, Brexit (51.2%; 326/637), referring to it as an act of self-harm.\u003c/p\u003e \u003cp\u003eMany users indicated they were proud of themselves (39.7%; 204/514) and others (31.7%; 163/514) for coping with self-harm and their recovery journey. Several encouraging tweets mentioned the duration of time that individuals refrained from engaging in self-harm. Some users also expressed the need to get help from others (14%; 72/514). Links to resources for individuals seeking help from self-harm were predominantly treatments or services (34.9%; 37/106) or hotlines (35.8%; 38/106) provided by organizations focused on self-harm. Links to mobile applications to manage self-harm or related mental health concerns such as anxiety, panic attacks, and depression were also observed in the corpus of tweets (11.3%; 12/106).\u003c/p\u003e \u003cp\u003eWith respect to the minor themes, the majority of tweets accepting self-harm promoted the behavior and glorified self-harm as a positive activity that should be engaged in. Tweets pertaining to self-harm terms contained either a single word or multiple words related to self-harm and without a coherent sentence structure.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTweet slants and categories within themes\u003c/h2\u003e \u003cp\u003eWith respect to tweet slants (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), most of the anti-self-harm tweets (40.4%; 1055/2611) fell under the theme of \u003cem\u003eUnderstanding self-harm\u003c/em\u003e. The same theme also had a large proportion of the total neutral slanted self-harm tweets (43.4%; 490/1128). While there were very few pro-self-harm tweets, most fell under the theme of \u003cem\u003eUnderstanding self-harm\u003c/em\u003e (33.6%; 36/107) and \u003cem\u003eReasons for self-harm\u003c/em\u003e (29.9%; 32/107). Within almost all the themes, anti-self-harm tweets were the most predominant. Tweets categorized under \u003cem\u003ePolitical\u003c/em\u003e (44.6%; 284/637), \u003cem\u003eComparisons\u003c/em\u003e (44.4%; 68/153), and \u003cem\u003eSelf-harm terms\u003c/em\u003e (81.3%; 39/48) were mostly neutral slanted. All themes under \u003cem\u003eAccepting self-harm\u003c/em\u003e were pro-self harm tweets (n\u0026thinsp;=\u0026thinsp;6). Conversely, none of the tweets that fell under the themes of \u003cem\u003eSelf-harm help resource\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;106), \u003cem\u003eSelf-harm terms\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;48), and \u003cem\u003eRepercussions of self-harm\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;12) contained pro-self-harm tweets.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegarding tweet categories (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), most personal opinions fell under the theme of \u003cem\u003eUnderstanding self-harm\u003c/em\u003e (38.5%; 417/1084) or \u003cem\u003eCalling out wrongdoings\u003c/em\u003e (25.4%; 275/1084). More than half of informative tweets were also categorized as \u003cem\u003eUnderstanding self-harm\u003c/em\u003e (77.6%; 729/939). Half of the tweets that were jokes or ridicule were \u003cem\u003eComparisons\u003c/em\u003e (50%; 36/72). Personal accounts and experiences were mostly coded under the themes of \u003cem\u003eSupport\u003c/em\u003e (35.2%; 341/969) or \u003cem\u003eUnderstanding self-harm\u003c/em\u003e (32.5%; 315/969). Tweets under advice-seeking mostly represented the theme \u003cem\u003eUnderstanding self-harm\u003c/em\u003e (46.7%; 56/120) or \u003cem\u003eSupport\u003c/em\u003e (29.2%; 35/120). Tweets that did not fall under any type were mostly \u003cem\u003ePolitical\u003c/em\u003e (79.6%; 527/662).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study aimed to develop an understanding of the types of tweets surrounding Twitter\u0026rsquo;s Suicide and Self-Harm policy. The findings indicated that the majority of tweets promoted a better understanding of self-harm, had an anti-self-harm slant, and were personal opinions.\u003c/p\u003e \u003cp\u003ePersonal opinions and informative tweets comprised the largest proportion of tweets intended to enhance understanding of self-harm. This finding highlights the importance of considering the types of information disseminated on the social media platform. Considering that a large proportion of social media users obtain their information online, the predominance of personal opinions may result in seemingly informative tweets being misleading or inaccurate. Indeed, the World Health Organization has recently coined the term \u003cem\u003eInfodemic\u003c/em\u003e, characterized by an overwhelming influx of information, including false or misleading content in both digital and physical realms, leading to confusion and potentially harmful health-related behaviors [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Although infodemics have been defined in the context of disease outbreaks, their relevance to self-harm has been demonstrated in the current study. While the number of neutral tweets significantly increased after policy enactment, there was also a simultaneous increase in both informative tweets and personal opinions. Although the policy may have encouraged discourse surrounding a better understanding of self-harm, the information also has the potential to promote a skewed understanding of the topic. Future studies should consider how different types of tweets aimed at improving a user\u0026rsquo;s understanding of self-harm are perceived by users, particularly those vulnerable to suicide and NSSI.\u003c/p\u003e \u003cp\u003eDespite concerns about how information is disseminated on Twitter, the high level of support expressed on the platform may provide insight into why many users may feel a sense of community and peer support [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The current study shed light on the dynamics of support - namely, that it provides a space for individuals to connect and support one another by sharing personal experiences with self-harm, providing resources to seek care, expressing specific reasons why self-harm may occur, and offering feedback on how these behaviors are portrayed in the media. While nearly all users called out the negative implications associated with self-harm, less than 1% posted pro-self-harm tweets that fell into this category. Many of these tweets accused social media of censoring their thoughts and opinions related to self-harm.\u003c/p\u003e \u003cp\u003eIn line with previous findings from the study authors and others, political tweets disseminated on the platform focused heavily on conflating Brexit with self-harm [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Nearly all of these tweets fell under none or more than one type and were either anti- or neutral-slanted. While the impact of calling social issues acts of self-harm has not been assessed, tweets that draw comparisons to self-harm may perpetuate mental health stigma [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. It is critical for future work to determine if reporting Brexit in this manner may have contributed, at least to some degree, to the raised suicide risk in Brexit-voting communities [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and increased anxiety and compromised mental health in migrants residing in the United Kingdom [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. It certainly raises the intriguing linguistic finding of this study, where the term self-harm extended beyond traditional definitions of the behavior.\u003c/p\u003e \u003cp\u003eA notable limitation of the study pertained to the self-harm language that was captured. Although the dissemination of self-harm content is a pervasive problem on social media, only about 3% of the total tweets analyzed were pro-self-harm. This number is substantially lower than reports of 9\u0026ndash;66% pro-self-harm content within other social media platforms [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In contrast, a recent report indicated a 500% increase in self-harm-related hashtags since October 2022 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The low number of pro-self-harm tweets in the current study may indicate that the ambiguous language of self-harm within social media platforms evolves in ways to bypass Suicide and Self-Harm policies [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. A conspicuous example is that the same report highlighted an increased use of hashtags like \u0026ldquo;#shtwt,\u0026rdquo; which is short for \u003cem\u003eS\u003c/em\u003eelf-\u003cem\u003eH\u003c/em\u003earm \u003cem\u003eTW\u003c/em\u003ei\u003cem\u003eT\u003c/em\u003eter [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Given the dynamic and ever-changing nature of this language, it may be challenging to delineate unique terms and examples over the long term. However, future studies may benefit from outlining specific strategies and methods to identify less obvious terms and hashtags related to self-harm.\u003c/p\u003e \u003cp\u003eTaken together, the current study demonstrated changes in the dialogue surrounding self-harm and how it may be impacted by policies targeted towards protecting users from exposure to potentially harmful content. While the policy may have increased conversations surrounding a better understanding of self-harm, it is important for social media platforms to clearly distinguish between what is factual and what is based on personal opinions. At the same time, personal opinions and the dissemination of personal accounts and experiences offer a space for peer support, which may benefit affected individuals.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eEM, HS, and WC were responsible for the study design. EM, KK, ST, and WC conducted data analysis. The main manuscript was written by EM, KK, and ST, and WC prepared all the study figures. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization (2023) Suicide. https://www.who.int/news-room/fact-sheets/detail/suicide\u003c/li\u003e\n\u003cli\u003eLiu RT (2023) The epidemiology of non-suicidal self-injury: lifetime prevalence, sociodemographic and clinical correlates, and treatment use in a nationally representative sample of adults in England. Psychol Med 53:274\u0026ndash;282. https://doi.org/10.1017/S003329172100146X\u003c/li\u003e\n\u003cli\u003eGillies D, Christou MA, Dixon AC, et al (2018) Prevalence and Characteristics of Self-Harm in Adolescents: Meta-Analyses of Community-Based Studies 1990\u0026ndash;2015. 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J Adolesc Health Off Publ Soc Adolesc Med 58:78\u0026ndash;84. https://doi.org/10.1016/j.jadohealth.2015.09.015\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Twitter, Self-harm, Suicide, Social media content, Content analysis, Suicide and self-harm policy, Tweet","lastPublishedDoi":"10.21203/rs.3.rs-3933060/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3933060/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The proliferation of suicide and self-harm content on social media platforms has emerged as a pressing concern in recent years, reflecting broader societal challenges surrounding mental health and online safety. In response to these concerns, platforms like Twitter (now “X”) have implemented policies aimed at curtailing the spread of such content and promoting user safety. The current study investigated the impact of Twitter's Suicide and Self-Harm Policy through a content analysis of tweets before and after its enactment, focusing on categorizing tweets according to slant, tweet category, and theme. A corpus of 3846 tweets was analyzed. Within this corpus, tweets spanning 32 weeks from October 18, 2018, to May 29, 2019, were selected. These dates were chosen to encompass approximately 16 weeks before and after the enactment of the policy on February 7, 2018. The analysis revealed notable shifts in the discourse surrounding self-harm, with discernible impacts attributed to the implementation of Twitter's policy. While the policy appeared to stimulate increased discussions aimed at fostering a better understanding of self-harm, it also underscored the necessity for social media platforms to delineate between factual information and personal opinions. However, the dissemination of personal accounts and experiences within these discussions served as a conduit for peer support, potentially offering invaluable assistance to individuals grappling with self-harm issues. Taken together, while policy interventions can stimulate constructive dialogue, careful consideration must be given to balancing factual accuracy with the provision of spaces for personal expression and support within online communities.","manuscriptTitle":"An examination of tweets posted before and after enactment of Twitter’s Suicide and Self-Harm Policy: a content analysis study.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-12 19:22:19","doi":"10.21203/rs.3.rs-3933060/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65d068eb-63da-4867-b24a-e2326c012fbd","owner":[],"postedDate":"February 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-20T20:59:47+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-12 19:22:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3933060","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3933060","identity":"rs-3933060","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}