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Attention-Based Bi-LSTM Model for Arabic Depression Classification
16 references·0 citing·42 second hop
Attention-Based Bi-LSTM Model for Arabic Depression Classification (2021)Attention-Based Bi-LSTM Model for Arabic …Automatic depression recognition using CNN with attention mechanism from videos (2020)Automatic depression recognit…A deep learning model for detecting mental illness from user content on social media (2020)A deep learning model for det…Early Detection of Depression: Social Network Analysis and Random Forest Techniques (2019)Early Detection of Depression…Detection of Suicide Ideation in Social Media Forums Using Deep Learning (2019)Detection of Suicide Ideation…Detecting Arabic Depressed Users from Twitter Data (2019)Detecting Arabic Depressed Us…Measuring the Latency of Depression Detection in Social Media (2018)Measuring the Latency of Depr…Deep Learning for Depression Detection of Twitter Users (2018)Deep Learning for Depression …Dynamic Multimodal Measurement of Depression Severity Using Deep Autoencoding (2017)Dynamic Multimodal Measuremen…Depression Detection via Harvesting Social Media: A Multimodal Dictionary Learning Solution (2017)Depression Detection via Harv…Depression detection using emotion artificial intelligence (2017)Depression detection using em…Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among U.S. young adults (2016)Use of multiple social media …ASSOCIATION BETWEEN SOCIAL MEDIA USE AND DEPRESSION AMONG U.S. YOUNG ADULTS (2016)ASSOCIATION BETWEEN SOCIAL ME…Cyberbullying, Depression, and Problem Alcohol Use in Female College Students: A Multisite Study (2015)Cyberbullying, Depression, an…Measuring Post Traumatic Stress Disorder in Twitter (2014)Measuring Post Traumatic Stre…Eye movement analysis for depression detection (2013)Eye movement analysis for dep…Suicide and Primary Affective Disorders (1970)Suicide and Primary Affective…Social network determinants of depression (2010)The Development and Psychometric Properties of LIWC2015 (2015)Detecting Stress Based on Social Interactions in Social Networks (2017)Machine Learning-Based Approach for Depression Detection in Twitter Using Content and Activity Features (2020)Predicting Depression via Social Media (2021)Mental-LLM (2024)Validation and Utility of a Self-report Version of PRIME-MD The PHQ Primary Care Study (1999)The PHQ-9 (2001)Cyberbullying: its nature and impact in secondary school pupils (2008)Cyberbullying in higher education: A literature review (2016)Cyber Stalking, Cyber Harassment, and Adult Mental Health: A Systematic Review (2020)Emotional Intelligence, Belongingness, and Mental Health in College Students (2020)Prevalence, Severity, and Comorbidity of 12-Month DSM-IV Disorders in the National Comorbidity Survey Replication (2005)Projections of Global Mortality and Burden of Disease from 2002 to 2030 (2006)Users of the world, unite! 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References

  • 2016ASSOCIATION BETWEEN SOCIAL MEDIA USE AND DEPRESSION AMONG U.S. YOUNG ADULTS1,110 cited
  • 1970Suicide and Primary Affective Disorders723 cited
  • 2016Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among U.S. young adults581 cited
  • 2017Depression Detection via Harvesting Social Media: A Multimodal Dictionary Learning Solution401 cited
  • 2018Deep Learning for Depression Detection of Twitter Users345 cited
  • 2014Measuring Post Traumatic Stress Disorder in Twitter316 cited
  • 2020A deep learning model for detecting mental illness from user content on social media303 cited
  • 2017Depression detection using emotion artificial intelligence270 cited
  • 2015Cyberbullying, Depression, and Problem Alcohol Use in Female College Students: A Multisite Study268 cited
  • 2019Detection of Suicide Ideation in Social Media Forums Using Deep Learning250 cited
  • 2019Early Detection of Depression: Social Network Analysis and Random Forest Techniques206 cited
  • 2017Dynamic Multimodal Measurement of Depression Severity Using Deep Autoencoding193 cited
  • 2020Automatic depression recognition using CNN with attention mechanism from videos179 cited
  • 2013Eye movement analysis for depression detection165 cited

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  • 2018Measuring the Latency of Depression Detection in Social Media127 cited
  • 2019Detecting Arabic Depressed Users from Twitter Data107 cited
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