A meta-analysis of linguistic markers of extraversion: Positive emotion and social process words

Abstract

Past literature has shown that extraversion is related to the use of positive emotion and social process words. However, the strength of the relationships varies substantially across studies. In this research, we conducted a meta-analysis (k = 37, N = 82,132) to estimate the overall effect size of the two linguistic correlates of extraversion. In addition, we tested potential moderators including demographic variables (e.g., age and gender) and communication contexts (e.g., synchronous vs. asynchronous, public vs. private). Our random effects models revealed a small correlation between extraversion and positive emotion words (r = .069, 95% CI = [.041, .096]), and a small correlation between extraversion and social process words (r = .077, 95% CI = [.044, .109]). In addition, the strength of the relationship between extraversion and positive emotion words varies across communication contexts, while the relationship between extraversion and social process words remains consistent across contexts. Our results suggest that positive emotion words and social process words are linguistic correlates of extraversion, but they are small in magnitude.

Beyond English: Considering Language and Culture in Psychological Text Analysis

“…The large number of existing studies speaks to the high relevance of this research, both in terms of establishing consensus between studies and in revealing relationships with other variables as support for concurrent validity with the results of established measures. However, recent studies have also raised important questions about the generalizability of existing findings beyond the original context of investigation, which has highlighted potential constraints on their validity in different languages and cultures (Garimella et al, 2016;Basnight-Brown and Altarriba, 2018;Jackson et al, 2019;Sánchez-Rada and Iglesias, 2019;Chen et al, 2020;Thompson et al, 2020;Dudãu and Sava, 2021). The results of the studies also indicate that the comparison and psychological interpretation of linguistic phenomena between different cultures and languages is subject to several fundamental challenges.…”

“…At the time of writing this article, 781 records were available on the Web of Science that contained "LIWC" or "Linguistic Inquiry and Word Count" as the topic, and more than twenty thousand records are listed on Google Scholar. In its current version, LIWC2015, the program offers an intuitive user interface and provides a simple and clear output of the results (Pennebaker et al, 2015), including a range of comparison possibilities (Chen et al, 2020). LIWC dictionaries have been translated and adapted into multiple languages, including Spanish (Ramírez-Esparza et al, 2007), French (Piolat et al, 2011), German (Wolf et al, 2008;Meier et al, 2019), Dutch (Boot et al, 2017;Van Wissen and Boot, 2017), Brazilian-Portuguese (Balage Filho et al, 2013;Carvalho et al, 2019), Chinese (Huang et al, 2012), Serbian (Bjekić et al, 2014), Italian (Agosti and Rellini, 2007), Russian (Kailer and Chung, 2007), Arabic (Hayeri, 2014), Japanese (Shibata et al, 2016), and Romanian (Dudãu and Sava, 2020).…”

“…In this sense, the communication context (text type, genre, register) is an important factor that can produce substantial variation both in the frequency of language features and in the associations with other variables, especially psychological ones (Pennebaker et al, 2007;Daems et al, 2013;Haider and Palmer, 2017;Biber and Conrad, 2019;Kučera et al, 2020;Dudãu and Sava, 2021). Differences in the sensitivity of LIWC for detecting psychological markers in different types of text (English only), were shown in the meta-analysis of Chen et al (2020), in which, for example, the strength of the relationship between extraversion and positive emotion words varied significantly and substantially across communication contexts (e.g., asynchronous/synchronous and public/private communication). Thus, if only one type of communication is used (e.g., only written language), it is difficult to estimate to what extent the translated dictionary has comparable validity for, for example, spoken communication.…”

Thedashangfeature in social media: a personality and justice theory perspective

“…The affect-as-information model suggests that people use affect as a heuristic and substitute it for objective criteria when making social judgments (Barsky and Kaplan, 2007). It has been found that extraversion is positively related to general happiness and positive affect (Chen et al, 2020). Individuals who need to make judgments under circumstances of uncertainty and incomplete information often rely on their feelings when they make decisions (Schwarz, 1990).…”

“…The underlying logic of these beneficial effects is that this group of people are more motivated, experience more positive affect and have greater interpersonal and leadership skills (Dietl and Kombeiz, 2020). Extraversion is also related to social interaction (Chen et al, 2020). Using smartphone sensing, Harari et al (2019) found that extraversion was positively correlated to the frequency of outgoing phone calls, text messages, use of messaging applications and social media.…”