Journal article

Latent human traits in the language of social media: An open-vocabulary approach

Vivek Kulkarni, Margaret L Kern, David Stillwell, Michel Kosinski, Sandra Matz, Lyle Ungar, Steven Skiena, H Andrew Schwartz

PLOS ONE | PUBLIC LIBRARY SCIENCE | Published : 2018

Abstract

Over the past century, personality theory and research has successfully identified core sets of characteristics that consistently describe and explain fundamental differences in the way people think, feel and behave. Such characteristics were derived through theory, dictionary analyses, and survey research using explicit self-reports. The availability of social media data spanning millions of users now makes it possible to automatically derive characteristics from behavioral data-language use-at large scale. Taking advantage of linguistic information available through Facebook, we study the process of inferring a new set of potential human traits based on unprompted language use. We subject ..

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Grants

Awarded by Templeton Religion Trust


Awarded by NSF


Funding Acknowledgements

Support for this research was provided by the Templeton Religion Trust grant TRT-0048 awarded to H. Andrew Schwartz and by NSF grants DBI-1355990 and IIS-1546113 awarded to Steven Skiena.