Abstract
Differences in self-concept have been observed across cultures. Participants from collectivist societies tend to describe themselves using social and relational attributes (mother, student, Arab) more frequently than their individualist counterparts, who tend to rely more heavily on personal attributes (fun, tall, beautiful). Much of this past research has relied on relatively small samples of college students, tasked with spontaneously reporting self-concepts in classroom settings. The present study re-examines these ideas using data extracted from Twitter, the popular social media platform. In analysis one, the Twitter biographies of individuals exclusively posting messages in English (N = 500) and those posting only in Arabic (N = 500) were content analyzed and quantified for differences in the frequency of personal versus social attribute use. Analysis two applied a bilingual word counting algorithm to the biographies of a larger sample of Twitter users (N = 242,162), exploring the relative frequency of social attributes, specifically familial roles (e.g. mother, father, daughter, son), across both English and Arabic users. In analysis one, the Twitter biographies of exclusive Arabic users contained significantly more social attributes than their English using counterparts. In analysis two, Arabic biographies contained significantly more familial references than their English language counterparts. These findings support the idea that cultural values may influence self-construal. Big data extracted from social media platforms appear to offer a useful means of exploring self-concept across cultures and languages.