Effects of gender and tie strength on Twitter interactions

We examine the connection between language, gender, and social relationships, as manifested through communication patterns in social media. Building on an analysis of 78,000 Twitter messages exchanged between 1,753 gender-coded couples, we quantitatively study how the gender composition of conversing users influences the linguistic style apparent in the messages. Using Twitter data, we also model and control for the strength of ties between conversing users. Our findings show that, in line with existing theories, women use more intensifier adverbs, pronouns, and emoticons, especially when communicating with other women. Our results extend the understanding of gender-driven language use in the semi-public settings of social media services, and suggest implications for theory and insights for sociolinguistics