Research on Text Sentiment Recognition Algorithm Integrated Enneagram and BiGRU-attention-CNN

Research on Text Sentiment Recognition Algorithm Integrated Enneagram and BiGRU-attention-CNN | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 30 April 2025 V1 Latest version Share on Research on Text Sentiment Recognition Algorithm Integrated Enneagram and BiGRU-attention-CNN Authors : Qingqing Wang and Wei Wu [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174599897.76003627/v1 178 views 130 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This study introduces a novel text sentiment analysis model that incorporates the enneagram personality theory into deep learning methodologies to address the oversight of traditional sentiment analysis tasks regarding the influence of individual personality traits on emotional expression. The model utilizes a bidirectional GRU, an attention mechanism, and a CNN for feature extraction, integrating these features with enneagram-based personality traits for predictive purposes. Experimental results showcase the high performance of the proposed model, particularly with the feature fusion technique based on residuals achieving accuracies of 91.4% and 90.6%, as well as F1 scores of 92.3% and 91.7% on the IMDB and MR datasets, respectively. Furthermore, the model exhibits strong generalization capabilities and robustness in practical scenarios. Supplementary Material File (research on text sentiment recognition algorithm integrated enneagram and bigru-attention-cnn.docx) Download 4.37 MB Information & Authors Information Version history V1 Version 1 30 April 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords bidirectional gru convolutional neural network emotion recognition enneagram Authors Affiliations Qingqing Wang Jilin Animation Institute View all articles by this author Wei Wu [email protected] Northeast Normal University College of Humanities and Sciences View all articles by this author Metrics & Citations Metrics Article Usage 178 views 130 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Qingqing Wang, Wei Wu. Research on Text Sentiment Recognition Algorithm Integrated Enneagram and BiGRU-attention-CNN. Authorea . 30 April 2025. DOI: https://doi.org/10.22541/au.174599897.76003627/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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