Applying Conversation Analysis Methods to Digital Discourse: A Review of the Literature

As communication modalities in the digital age have expanded, so too have the research approaches used to understand these new forms of discourse. Conversation analysis (CA), a methodology focused on the study of the systematic and organized nature of everyday and institutionalized talk (Sacks, 1992), is one such approach. While scholars have debated how and to what extent CA can effectively be applied to online “talk”, researchers in diverse fields, including educational technology, journalism and counseling have used CA to better understand various forms of digital discourse (e.g. Steensen, 2014). Previous studies have raised questions around how traditional CA concepts such as transcription, turn-taking and repair function in these contexts (e.g. Meredith & Potter, 2013). In this presentation we will share findings from our literature review of 81 peer-reviewed empirical articles which used CA to study text-based digital discourse. Analysis is focused on 1) describing the disciplines in which CA is being used; 2) identifying types of data under analysis; and 3) categorizing conversational features used to describe social actions. Preliminary findings show that most studies take place in language, communication, health and/or education contexts analyzing a variety of data types. Our intensive analysis is exploring how conversational features are being evoked to make sense of social actions, e.g. how coherence is maintained in decision-making environments, how openings and closings are managed in counseling environments, and how repairs occur in language learning. Findings from our review can help guide researchers in how best to take up CA methods in understanding digital discourse.