J
Johannes C. Eichstaedt
Researcher at Stanford University
Publications - 84
Citations - 6054
Johannes C. Eichstaedt is an academic researcher from Stanford University. The author has contributed to research in topics: Social media & Personality. The author has an hindex of 26, co-authored 66 publications receiving 4457 citations. Previous affiliations of Johannes C. Eichstaedt include University of Pennsylvania.
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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
Detecting depression and mental illness on social media: an integrative review
Sharath Chandra Guntuku,David B. Yaden,Margaret L. Kern,Lyle H. Ungar,Johannes C. Eichstaedt +4 more
TL;DR: Automated detection methods may help to identify depressed or otherwise at-risk individuals through the large-scale passive monitoring of social media, and in the future may complement existing screening procedures.
Journal ArticleDOI
Psychological Language on Twitter Predicts County-Level Heart Disease Mortality
Johannes C. Eichstaedt,Hansen Andrew Schwartz,Margaret L. Kern,Gregory Park,Darwin R. Labarthe,Raina M. Merchant,Sneha Jha,Megha Agrawal,Lukasz Dziurzynski,Maarten Sap,Christopher Weeg,Emily E. Larson,Lyle H. Ungar,Martin E. P. Seligman +13 more
TL;DR: Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level.
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.