Ambient affiliation: A linguistic perspective on Twitter

TLDR

Electronic discourse is shifting from informal conversation to searchable talk. The article investigates how language builds community on Twitter. Using Systemic Functional Linguistics, the authors analyzed 45,000 tweets from the 24 hours after Obama’s 2008 election victory to examine evaluative language that affiliates users. Hashtags function as linguistic markers that make tweets searchable and amplify calls for affiliation with expressed values.

Abstract

This article explores how language is used to build community with the microblogging service, Twitter (www.twitter.com). Systemic Functional Linguistic (SFL), a theory of language use in its social context, is employed to analyse the structure and meaning of ‘tweets’ (posts to Twitter) in a corpus of 45,000 tweets collected in the 24 hours after the announcement of Barak Obama’s victory in the 2008 US presidential elections. This analysis examines the evaluative language used to affiliate in tweets. The article shows how a typographic convention, the hashtag, has extended its meaning potential to operate as a linguistic marker referencing the target of evaluation in a tweet (e.g. #Obama). This both renders the language searchable and is used to upscale the call to affiliate with values expressed in the tweet. We are currently witnessing a cultural shift in electronic discourse from online conversation to such ‘searchable talk’.