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Detecting Arabic Depressed Users from Twitter Data
9 references·3 citing·48 second hop
Detecting Arabic Depressed Users from Twitter Data (2019)Detecting Arabic Depressed Users from Twi…Predicting Depression via Social Media (2021)Predicting Depression via Soc…Stigma associated with mental illness and its treatment in the Arab culture: A systematic review (2018)Stigma associated with mental…Predicting Depression Levels Using Social Media Posts (2017)Predicting Depression Levels …Identifying Depression on Twitter (2016)Identifying Depression on Twi…Quantifying Mental Health Signals in Twitter (2014)Quantifying Mental Health Sig…Measuring Post Traumatic Stress Disorder in Twitter (2014)Measuring Post Traumatic Stre…Social media as a measurement tool of depression in populations (2013)Social media as a measurement…Depression: A Global Public Health Concern (2012)Depression: A Global Public H…The CES-D Scale (1977)The CES-D ScaleDepression detection for twitter users using sentiment analysis in English and Arabic tweets (2023)Depression detection for twit…Text-based Depression Detection on Social Media Posts: A Systematic Literature Review (2021)Text-based Depression Detecti…Attention-Based Bi-LSTM Model for Arabic Depression Classification (2021)Attention-Based Bi-LSTM Model…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)Mental-LLM (2024)The Epidemiology of Major Depressive Disorder (2003)Projections of Global Mortality and Burden of Disease from 2002 to 2030 (2006)Internet Research in Psychology (2014)Psychological Language on Twitter Predicts County-Level Heart Disease Mortality (2015)Social Networking Sites, Depression, and Anxiety: A Systematic Review (2016)A new scale of social desirability independent of psychopathology. 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(1984)Mental Health Discourse on reddit: Self-Disclosure, Social Support, and Anonymity (2014)Annual Research Review: Adolescent mental health in the digital age: facts, fears, and future directions (2020)Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice (2020)Suicide Prevention Strategies (2005)Detecting the magnitude of depression in Twitter users using sentiment analysis (2019)Analysis of Deep Learning Techniques for Early Detection of Depression on Social Media Network - A Comparative Study (2021)Depression Detection Using Machine Learning Techniques on Twitter Data (2021)Does the DSM-IV Clinical Significance Criterion for Major Depression Reduce False Positives? Evidence From the National Comorbidity Survey Replication (2010)Depression Detection from Social Media Text Analysis using Natural Language Processing Techniques and Hybrid Deep Learning Model (2022)Depression detection using emotional artificial intelligence and machine learning: A closer review (2022)Depression Detection From Social Networks Data Based on Machine Learning and Deep Learning Techniques: An Interrogative Survey (2023)Stigma: Notes on the Management of Spoiled Identity. (1964)A user's guide to the General Health Questionnaire (1988)Short screening scales to monitor population prevalences and trends in non-specific psychological distress (2002)A longitudinal cohort study to explore the relationship between depression, anxiety and academic performance among Emirati university students (2020)Mental illness and help-seeking behaviours among Middle Eastern cultures: A systematic review and meta-synthesis of qualitative data (2023)Understanding experiences of mental health help-seeking in Arab populations around the world: a systematic review and narrative synthesis (2023)Use of mental health services for anxiety, mood, and substance disorders in 17 countries in the WHO world mental health surveys (2007)Detecting suicidality on Twitter (2015)Artificial intelligence assisted tools for the detection of anxiety and depression leading to suicidal ideation in adolescents: a review (2022)OPI@LT-EDI-ACL2022: Detecting Signs of Depression from Social Media Text using RoBERTa Pre-trained Language Models (2022)Detection of Depression Severity in Social Media Text Using Transformer-Based Models (2025)A therapeutic application of the experience sampling method in the treatment of depression: a randomized controlled trial (2014)Recognizing Depression from Twitter Activity (2015)A comprehensive meta-analysis of interpretation biases in depression (2017)
this work references cited by second hop

References

  • 1977The CES-D Scale53,239 cited
  • 2021Predicting Depression via Social Media1,582 cited
  • 2012Depression: A Global Public Health Concern998 cited
  • 2014Quantifying Mental Health Signals in Twitter722 cited
  • 2013Social media as a measurement tool of depression in populations497 cited
  • 2014Measuring Post Traumatic Stress Disorder in Twitter316 cited
  • 2018Stigma associated with mental illness and its treatment in the Arab culture: A systematic review286 cited
  • 2017Predicting Depression Levels Using Social Media Posts174 cited
  • 2016Identifying Depression on Twitter113 cited

Cited by

  • 2021Text-based Depression Detection on Social Media Posts: A Systematic Literature Review89 cited
  • 2023Depression detection for twitter users using sentiment analysis in English and Arabic tweets53 cited
  • 2021Attention-Based Bi-LSTM Model for Arabic Depression Classification53 cited

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