World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
89
Citations
40546
World Ranking
637
National Ranking
339

Overview

Lyle H. Ungar is affiliated with the University of Pennsylvania in the United States. Their research primarily spans the field of Psychology, with a focus on several subfields including Artificial Intelligence, Social Psychology, Experimental and Cognitive Psychology, Applied Psychology, and Sociology and Political Science.

Their work explores a range of topics such as Mental Health via Writing, Mental Health Research Topics, Digital Mental Health Interventions, Machine Learning in Healthcare, Topic Modeling, Misinformation and Its Impacts, and Sentiment Analysis and Opinion Mining.

Ungar has contributed to numerous publication venues, with frequent appearances in:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Proceedings of the National Academy of Sciences
  • Scientific Reports

Some of their recent papers include:

  • "Megastudies improve the impact of applied behavioural science" (2021), published in Nature
  • "Characterizing Geographic Variation in Well-Being Using Tweets" (2021), published in Proceedings of the International AAAI Conference on Web and Social Media
  • "Estimating geographic subjective well-being from Twitter: A comparison of dictionary and data-driven language methods" (2020), published in Proceedings of the National Academy of Sciences
  • "Analyzing Personality through Social Media Profile Picture Choice" (2021), published in Proceedings of the International AAAI Conference on Web and Social Media
  • "The emotional and mental health impact of the murder of George Floyd on the US population" (2021), published in Proceedings of the National Academy of Sciences

Lyle H. Ungar collaborates frequently with a group of co-authors including Salvatore Giorgi, Sharath Chandra Guntuku, Brenda Curtis, Johannes C. Eichstaedt, and H. Andrew Schwartz.

Best Publications

  • Methods and metrics for cold-start recommendations

    Andrew I. Schein;Alexandrin Popescul;Lyle H. Ungar;David M. Pennock

  • Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach

    H. Andrew Schwartz;Johannes C. Eichstaedt;Margaret L. Kern;Lukasz Dziurzynski

  • Efficient clustering of high-dimensional data sets with application to reference matching

    Andrew McCallum;Kamal Nigam;Lyle H. Ungar

  • A hybrid neural network‐first principles approach to process modeling

    Dimitris C. Psichogios;Lyle H. Ungar

  • Clustering Methods for Collaborative Filtering

    Lyle H. Ungar;Dean P. Foster

  • Twitter as a Tool for Health Research: A Systematic Review

    Lauren Sinnenberg;Alison M. Buttenheim;Kevin Padrez;Christina Mancheno

  • Detecting depression and mental illness on social media: an integrative review

    Sharath Chandra Guntuku;David B Yaden;Margaret L Kern;Lyle H Ungar

  • Facebook language predicts depression in medical records.

    Johannes C. Eichstaedt;Robert J. Smith;Raina M. Merchant;Lyle H. Ungar

  • Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments

    Alexandrin Popescul;Lyle H. Ungar;David M. Pennock;Steve Lawrence

  • Iterative Combinatorial Auctions: Theory and Practice

    David C. Parkes;Lyle H. Ungar

  • Iterative combinatorial auctions: achieving economic and computational efficiency

    David Christopher Parkes;Lyle H. Ungar

  • Active learning for logistic regression: an evaluation

    Andrew Ian Schein;Lyle H. Ungar

  • Statistical Relational Learning for Link Prediction

    Alexandrin Popescul;Lyle H. Ungar

  • Psychological Strategies for Winning a Geopolitical Forecasting Tournament

    Barbara Mellers;Lyle Ungar;Jonathan Baron;Jaime Ramos

  • EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks

    Muhammad Abdul-Mageed;Lyle H. Ungar

  • Using radial basis functions to approximate a function and its error bounds

    J.A. Leonard;M.A. Kramer;L.H. Ungar

  • Multi-View Learning of Word Embeddings via CCA

    Paramveer Dhillon;Dean P Foster;Lyle H. Ungar

  • Beyond Binary Labels: Political Ideology Prediction of Twitter Users

    Daniel Preoţiuc-Pietro;Ye Liu;Daniel Hopkins;Lyle Ungar

  • Direct and indirect model based control using artificial neural networks

    Dimitris C. Psichogios;Lyle H. Ungar

  • Characterizing geographic variation in well-being using tweets

    Hansen Andrew Schwartz;Johannes C. Eichstaedt;Margaret L. Kern;Lukasz Dziurzynski

  • Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining

    Tina Eliassi-Rad;Lyle Ungar;Mark Craven;Dimitrios Gunopulos

Frequent Co-Authors

H. Andrew Schwartz
H. Andrew Schwartz Stony Brook University
Johannes C. Eichstaedt
Johannes C. Eichstaedt Stanford University
Dean P. Foster
Dean P. Foster Amazon (United States)
Margaret L. Kern
Margaret L. Kern University of Melbourne
Barbara A. Mellers
Barbara A. Mellers University of Pennsylvania
Martin E. P. Seligman
Martin E. P. Seligman University of Pennsylvania
Philip E. Tetlock
Philip E. Tetlock University of Pennsylvania
David Stillwell
David Stillwell University of Cambridge
Maarten Sap
Maarten Sap Carnegie Mellon University
Michal Kosinski
Michal Kosinski Stanford University

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