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Social Sciences and Humanities

D-Index
70
Citations
18285
World Ranking
774
National Ranking
369

Overview

Munmun De Choudhury is affiliated with the Georgia Institute of Technology in the United States. Their research primarily spans the fields of psychology and social sciences, with a significant focus on social psychology, applied psychology, sociology and political science, artificial intelligence, and experimental and cognitive psychology. The scholar's work concentrates heavily on mental health topics, particularly through digital and social media platforms.

Their main research topics include:

  • Mental Health via Writing
  • Digital Mental Health Interventions
  • Mental Health Research Topics
  • Misinformation and Its Impacts
  • Hate Speech and Cyberbullying Detection
  • Impact of Technology on Adolescents
  • Suicide and Self-Harm Studies

Among recent publications, key papers authored or co-authored by the researcher include:

  • "Predicting Depression via Social Media," 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "Methods in predictive techniques for mental health status on social media: a critical review," 2020, npj Digital Medicine
  • "Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom," 2021, Biological Psychiatry Cognitive Neuroscience and Neuroimaging
  • "From promise to practice: towards the realisation of AI-informed mental health care," 2022, The Lancet Digital Health
  • "Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media," 2020, Journal of Medical Internet Research

Their collaboration network includes frequent co-authors such as Koustuv Saha, Michael L. Birnbaum, Navin Kumar, Gregory D. Abowd, and Sachin R. Pendse. This indicates interdisciplinary and cross-institutional partnerships predominantly around mental health and technology use in social contexts.

Publication venues that feature the researcher's work repeatedly are:

  • arXiv (Cornell University)
  • Proceedings of the ACM on Human-Computer Interaction
  • Proceedings of the International AAAI Conference on Web and Social Media
  • JMIR Mental Health
  • JMIR Formative Research

The research portfolio shows an integration of psychological theories with artificial intelligence approaches to understand and intervene in mental health through social media and digital behavior analysis. This work spans foundational studies in psychology and social sciences while leveraging computational methodologies to address contemporary health issues.

Best Publications

  • Predicting Depression via Social Media

    Munmun De Choudhury;Michael Gamon;Scott Counts;Eric Horvitz

  • Mental Health Discourse on reddit: Self-Disclosure, Social Support, and Anonymity

    Munmun De Choudhury;Sushovan De

  • Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media

    Munmun De Choudhury;Emre Kiciman;Mark Dredze;Glen Coppersmith

  • Social media as a measurement tool of depression in populations

    Munmun De Choudhury;Scott Counts;Eric Horvitz

  • Predicting postpartum changes in emotion and behavior via social media

    Munmun De Choudhury;Scott Counts;Eric Horvitz

  • Methods in predictive techniques for mental health status on social media: a critical review.

    Stevie Chancellor;Munmun De Choudhury

  • Characterizing and predicting postpartum depression from shared facebook data

    Munmun De Choudhury;Scott Counts;Eric J. Horvitz;Aaron Hoff

  • Understanding Social Media Disclosures of Sexual Abuse Through the Lenses of Support Seeking and Anonymity

    Nazanin Andalibi;Oliver L. Haimson;Munmun De Choudhury;Andrea Forte

  • Automatic construction of travel itineraries using social breadcrumbs

    Munmun De Choudhury;Moran Feldman;Sihem Amer-Yahia;Nadav Golbandi

  • Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom.

    Ellen E. Lee;John Torous;Munmun De Choudhury;Colin A. Depp

  • Seeking and sharing health information online: comparing search engines and social media

    Munmun De Choudhury;Meredith Ringel Morris;Ryen W. White

  • How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media

    Munmun De Choudhury;Yu Ru Lin;Hari Sundaram;K. Selçuk Candan

  • Finding and assessing social media information sources in the context of journalism

    Nicholas Diakopoulos;Munmun De Choudhury;Mor Naaman

  • #thyghgapp: Instagram Content Moderation and Lexical Variation in Pro-Eating Disorder Communities

    Stevie Chancellor;Jessica Annette Pater;Trustin Clear;Eric Gilbert

  • Inferring relevant social networks from interpersonal communication

    Munmun De Choudhury;Winter A. Mason;Jake M. Hofman;Duncan J. Watts

  • The Language of Social Support in Social Media and its Effect on Suicidal Ideation Risk.

    Munmun De Choudhury;Emre Kiciman

  • Quantifying and Predicting Mental Illness Severity in Online Pro-Eating Disorder Communities

    Stevie Chancellor;Zhiyuan Lin;Erica L. Goodman;Stephanie Zerwas

  • Not All Moods Are Created Equal! Exploring Human Emotional States in Social Media

    Munmun De Choudhury;Scott Counts;Michael Gamon

  • A Taxonomy of Ethical Tensions in Inferring Mental Health States from Social Media

    Stevie Chancellor;Michael L. Birnbaum;Eric D. Caine;Vincent M. B. Silenzio

  • Social Media Participation in an Activist Movement for Racial Equality

    Munmun De Choudhury;Shagun Jhaver;Benjamin Sugar;Ingmar Weber

Frequent Co-Authors

Gloria Mark
Gloria Mark University of California, Irvine
Andrew T. Campbell
Andrew T. Campbell Dartmouth College
Sidney K. D'Mello
Sidney K. D'Mello University of Colorado Boulder
John Torous
John Torous Harvard Medical School
Stephen M. Schueller
Stephen M. Schueller University of California, Irvine
Louis Tay
Louis Tay Purdue University West Lafayette
Helen Christensen
Helen Christensen University of New South Wales
Laura M. Thornton
Laura M. Thornton University of North Carolina at Chapel Hill

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