H
H. Andrew Schwartz
Researcher at Stony Brook University
Publications - 124
Citations - 5838
H. Andrew Schwartz is an academic researcher from Stony Brook University. The author has contributed to research in topics: Computer science & Social media. The author has an hindex of 31, co-authored 100 publications receiving 4158 citations. Previous affiliations of H. Andrew Schwartz include University of Illinois at Urbana–Champaign & University of Pennsylvania.
Papers
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Journal ArticleDOI
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,Stephanie M. Ramones,Megha Agrawal,Achal Shah,Michal Kosinski,David Stillwell,Martin E. P. Seligman,Lyle H. Ungar +10 more
TL;DR: This represents the largest study, by an order of magnitude, of language and personality, and found striking variations in language with personality, gender, and age.
Journal ArticleDOI
Automatic personality assessment through social media language.
Gregory Park,H. Andrew Schwartz,Johannes C. Eichstaedt,Margaret L. Kern,Michal Kosinski,David Stillwell,Lyle H. Ungar,Martin E. P. Seligman +7 more
TL;DR: Results indicated that language-based assessments can constitute valid personality measures: they agreed with self-reports and informant reports of personality, added incremental validity over informant reports, adequately discriminated between traits, and were stable over 6-month intervals.
Journal ArticleDOI
Facebook language predicts depression in medical records.
Johannes C. Eichstaedt,Robert J. Smith,Raina M. Merchant,Lyle H. Ungar,Patrick Crutchley,Daniel Preoţiuc-Pietro,David A. Asch,David A. Asch,H. Andrew Schwartz +8 more
TL;DR: It is shown that the content shared by consenting users on Facebook can predict a future occurrence of depression in their medical records, and language predictive of depression includes references to typical symptoms, including sadness, loneliness, hostility, rumination, and increased self-reference.
Proceedings ArticleDOI
Towards Assessing Changes in Degree of Depression through Facebook
H. Andrew Schwartz,Johannes C. Eichstaedt,Margaret L. Kern,Gregory Park,Maarten Sap,David Stillwell,Michal Kosinski,Lyle H. Ungar +7 more
TL;DR: A regression model is developed that predicts users’ degree of depression based on their Facebook status updates, and shows the potential to study factors driving individuals’ level of depression by looking at its most highly correlated language features.
Journal ArticleDOI
Yelp Reviews Of Hospital Care Can Supplement And Inform Traditional Surveys Of The Patient Experience Of Care
Benjamin L. Ranard,Rachel M. Werner,Tadas Antanavicius,H. Andrew Schwartz,Robert J. Smith,Zachary F. Meisel,David A. Asch,Lyle H. Ungar,Raina M. Merchant +8 more
TL;DR: The large collection of patient- and caregiver-centered experiences found on Yelp can be analyzed with natural language processing methods, identifying for policy makers the measures of hospital quality that matter most to patients and caregivers.