Paulus2016
| Paulus2016 | |
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| BibType | ARTICLE |
| Key | Paulus2016 |
| Author(s) | Trena Paulus, Amber Warren, Jessica Nina Lester |
| Title | Applying conversation analysis methods to online talk: A literature review |
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| Tag(s) | EMCA, Online Interaction, Computer-mediated communication, In press, Literature review |
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| Year | 2016 |
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| Journal | Discourse, Context & Media |
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| URL | Link |
| DOI | doi:10.1016/j.dcm.2016.04.001 |
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Abstract
While researchers have used conversation analysis (CA) methods to understand online talk since the 1990s, to date there has been no systematic review of these studies to better understand this methodological development. This article presents a comprehensive literature review of 89 peer-reviewed journal articles reporting findings of empirical studies using CA to understand social interaction online. In this review, we describe who is conducting this type of research, the contexts in which CA has been used to make sense of text-based online talk, and where such studies are being published. We also identify the “fundamental” conversational structures researchers are drawing upon in making sense of online talk as social interaction. Findings show that studies are using CA to understand “mundane” conversational contexts, as well as institutional talk from educational, counseling and workplace settings. The number of such studies are increasing and are being conducted by an international network of researchers across a variety of disciplines. The data is most often described as synchronous or asynchronous, with a slow increase in attention to social media data. Publication outlets are mostly language-based and/methodological journals. Analysis revealed four main aims: (1) comparing online and face-to-face talk, (2) understanding how coherence is maintained, (3) understanding how participants deal with trouble, and (4) understanding how social actions are accomplished asynchronously, This review contributes to the overall understanding of the methodological development of CA, offering useful insights for those interested in using it to understand social interaction as it occurs online.
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