Journal article

Regional personality assessment through social media language

Salvatore Giorgi, Khoa Le Nguyen, Johannes C Eichstaedt, Margaret L Kern, David B Yaden, Michal Kosinski, Martin EP Seligman, Lyle H Ungar, H Andrew Schwartz, Gregory Park



OBJECTIVE: We explore the personality of counties as assessed through linguistic patterns on social media. Such studies were previously limited by the cost and feasibility of large-scale surveys; however, language-based computational models applied to large social media datasets now allow for large-scale personality assessment. METHOD: We applied a language-based assessment of the five factor model of personality to 6,064,267 U.S. Twitter users. We aggregated the Twitter-based personality scores to 2,041 counties and compared to political, economic, social, and health outcomes measured through surveys and by government agencies. RESULTS: There was significant personality variation across cou..

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Awarded by Templeton Religion Trust

Funding Acknowledgements

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Preparation of this manuscript was supported by the Robert Wood Johnson Foundation's Pioneer Portfolio, the "Exploring Concepts of Positive Health" grant awarded to Martin Seligman, by TRT0048: The World Well--Being Project: Measuring well-being using big data, social media, and language analyses from the Templeton Religion Trust, and by the University of Pennsylvania Positive Psychology Center