Virtual Gender Identity: The Linguistic Assimilation to Gendered Avatars in Computer-Mediated Communication

Abstract

This research examined how individuals’ gendered avatar might alter their use of gender-based language (i.e., references to emotion, apologies, and tentative language) in text-based computer-mediated communication. Specifically, the experiment tested if men and women would linguistically assimilate a virtual gender identity intimated by randomly assigned gendered avatars (either matched or mismatched to their true gender). Results supported the notion that gender-matched avatars increase the likelihood of gender-typical language use, whereas gender-mismatched avatars promoted countertypical language, especially among women. The gender of a partner’s avatar, however, did not influence participants’ language. Results generally comport with self-categorization theory’s gender salience explanation of gender-based language use.