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. 2022 Jun;90(3):405-425.
doi: 10.1111/jopy.12674. Epub 2021 Oct 11.

Regional personality assessment through social media language

Salvatore Giorgi  1 , Khoa Le Nguyen  2 , Johannes C Eichstaedt  3 , Margaret L Kern  4 , David B Yaden  5 , Michal Kosinski  6 , Martin E P Seligman  7 , Lyle H Ungar  1 , H Andrew Schwartz  8 , Gregory Park  7
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Regional personality assessment through social media language

Salvatore Giorgi et al. J Pers. 2022 Jun.

Abstract

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 counties. Openness to experience was higher on the coasts, conscientiousness was uniformly spread, extraversion was higher in southern states, agreeableness was higher in western states, and emotional stability was highest in the south. Across 13 outcomes, language-based personality estimates replicated patterns that have been observed in individual-level and geographic studies. This includes higher Republican vote share in less agreeable counties and increased life satisfaction in more conscientious counties.

Conclusions: Results suggest that regions vary in their personality and that these differences can be studied through computational linguistic analysis of social media. Furthermore, these methods may be used to explore other psychological constructs across geographies.

Keywords: big data; language; measurement; personality assessment; social media.

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Conflict of interest statement

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Process flow for developing predictive models and applying them to county-level language.
Figure 2.
Figure 2.
County-level personality dimensions from language-based assessments (white indicates not enough data). Full interactive maps available at map.wwbp.org.
Figure 3.
Figure 3.
Convergent validity of County-level language-based personality estimates as a function of the minimum number of self-reports and Twitter users per county.
See this image and copyright information in PMC

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References

    1. Allik J, & McCrae RR (2004). Toward a geography of personality traits: Patterns of profiles across 36 cultures. Journal of Cross Cultural Psychology, 35, 13–28.
    1. Atkins DC, Rubin TN, Steyvers M, Doeden MA, Baucom BR, & Christensen A (2012). Topic models: A novel method for modeling couple and family text data. Journal of Family Psychology, 26, 816–827. 10.1037/a0029607 - DOI - PMC - PubMed
    1. Arbia G (2014). A primer for spatial econometrics with applications in R. Palgrave Macmillan.
    1. Back MD, Stopfer JM, Vazire S, Gaddis S, Schmukle SC, Egloff B, & Gosling SD (2010). Facebook profiles reflect actual personality, not self-idealization. Psychological Science, 21, 372–374. 10.1177/0956797609360756 - DOI - PubMed
    1. Benjamini Y, & Hochberg Y (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57(1), 289–300.

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