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Yla R. Tausczik
Researcher at University of Maryland, College Park
Publications - 37
Citations - 5579
Yla R. Tausczik is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Hidden profile & Social media. The author has an hindex of 14, co-authored 37 publications receiving 4336 citations. Previous affiliations of Yla R. Tausczik include University of California, Berkeley & Carnegie Mellon University.
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Journal ArticleDOI
The psychological meaning of words: LIWC and computerized text analysis methods
TL;DR: The Linguistic Inquiry and Word Count (LIWC) system as discussed by the authors is a text analysis system that counts words in psychologically meaningful categories to detect meaning in a wide variety of experimental settings, including to show attentional focus, emotionality, social relationships, thinking styles and individual differences.
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An empirical test of partner choice mechanisms in a wild legume–rhizobium interaction
Ellen L. Simms,D. Lee Taylor,Joshua Povich,Richard P. Shefferson,Joel L. Sachs,M Urbina,Yla R. Tausczik +6 more
TL;DR: The survey of wild-grown plants showed that larger nodules house more Bradyrhizobia, indicating that plants may prevent the spread of exploitation by favouring better cooperators, and testing partner choice theory in a wild legume–rhizobium symbiosis.
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Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI
Dakuo Wang,Justin D. Weisz,Michael Muller,Parikshit Ram,Werner Geyer,Casey Dugan,Yla R. Tausczik,Horst Samulowitz,Alexander G. Gray +8 more
TL;DR: The authors conducted interviews with 20 data scientists who work at a large, multinational technology company and practice data science in various business settings to understand their current work practices and how these practices might change with AutoAI.
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Public anxiety and information seeking following the H1N1 outbreak: blogs, newspaper articles, and Wikipedia visits.
TL;DR: The results show that the public reaction to H1N1 was rapid and short-lived, and analysis of web behavior can provide a source of naturalistic data on the level and changing pattern of public anxiety and information seeking following the outbreak of a public health emergency.
Journal ArticleDOI
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI
Dakuo Wang,Justin D. Weisz,Michael Muller,Parikshit Ram,Werner Geyer,Casey Dugan,Yla R. Tausczik,Horst Samulowitz,Alexander G. Gray +8 more
TL;DR: This paper conducted interviews with 20 data scientists who work at a large, multinational technology company and practice data science in various business settings to understand their current work practices and how these practices might change with AutoAI.