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JournalISSN: 2211-6958

Discourse, Context and Media 

Elsevier BV
About: Discourse, Context and Media is an academic journal published by Elsevier BV. The journal publishes majorly in the area(s): Social media & Discourse analysis. It has an ISSN identifier of 2211-6958. Over the lifetime, 482 publications have been published receiving 6324 citations. The journal is also known as: Discourse, context and media.

Papers published on a yearly basis

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Journal ArticleDOI
TL;DR: The development of methods that are inherently suited for subjecting online interaction to the kind of rigorous analysis that conversation analysts have applied to talk of all kinds for several decades are discussed.
Abstract: This paper introduces the work of the MOOD (Microanalysis Of Online Data) network, an interdisciplinary association of academic researchers exploring ways of conducting close qualitative analyses of online interaction. Despite the fact that much online interaction meets the criteria for ‘conversation’, conversation analysis (CA) has only recently begun to grow and flourish as a methodology for analysing the overwhelming quantity of material that in many cases sits in archive form, visible to millions, on the Internet. We discuss the development of methods that are inherently suited for subjecting online interaction to the kind of rigorous analysis that conversation analysts have applied to talk of all kinds for several decades. We go on to explore the fundamental challenges that online data pose for CA, the value of many CA techniques for online analysis, and the possibilities of developing bespoke modes of analysis that are crafted for use with specific forms of online data (e.g. ‘tweets’ on Twitter ).

158 citations

Journal ArticleDOI
TL;DR: The authors investigated the generic structure of hotel responses to customer complaints posted on TripAdvisor and found that responses from businesses replying to user-generated reviews tend to be highly formulaic and conventionalized, with thanking and apologizing among the most common moves identified.
Abstract: In this study we investigate the generic structure of hotel responses to customer complaints posted on popular travel website, TripAdvisor. Extending the genre analytic notion of rhetorical moves ( Swales, 1981 , Swales, 2004 ) to this computer-mediated text type, we analyzed 80 hotel replies that were posted in response to online consumer complaints. Our analysis of the responses of 4- and 5-star hotels located in 4 popular urban tourist destinations in China indicates that ten move types are commonly found in this genre, with eight of these appearing in the majority of reviews. These results suggest that online responses from businesses replying to user-generated reviews tend to be highly formulaic and conventionalized, with thanking and apologizing among the most common moves identified. However, we also found considerable variation with respect to how specific hotels were about addressing the problem(s) discussed in the original customer complaint, as well as the extent to which hotel management indicated having taken actions to correct those problems. Finally, our study found that in this set of responses, hotel personnel tended to emphasize a corporate (rather than personal) identity when constructing responses to complaints. The study׳s findings provide insights into some of the ways in which businesses are managing consumer dissatisfaction online.

123 citations

Journal ArticleDOI
TL;DR: In this paper, a discourse analytical perspective is adopted to examine the visual-discursive features of Internet memes in relation to the candidates for the 2016 U.S presidential election, focusing on how memes attempt to create a negative view of the candidates and reduce their legitimacy as presidential candidates.
Abstract: Internet memes are a contemporary phenomenon situated at the nexus of language, society, and digital communication, and represent a relatively new form of participatory culture that can offer certain demographics an opportunity for political expression, engagement and participation which otherwise might not have been accessible. This article adopts a discourse analytical perspective to examine the visual-discursive features of Internet memes in relation to the candidates for the 2016 U.S presidential election – Donald Trump and Hillary Clinton. Specifically, memes are analyzed in line with Van Leeuwen׳s (2007) framework for the analysis of legitimizing discourse in relation to how they de-legitimize. That is, the focus is on how memes attempt to create a negative view of the candidates and reduce their legitimacy as presidential candidates. The analysis reveals that the (de)legitimization strategies of authorization, moral evaluation, rationalization and mythopoesis are all evident within Internet memes.

118 citations

Journal ArticleDOI
TL;DR: This article used topic modeling and critical discourse analysis to examine patterns of representation around the words Muslim and Islam in a 105 million word corpus of a large Swedish Internet forum from 2000 to 2013.
Abstract: This article combines topic modeling and critical discourse analysis to examine patterns of representation around the words Muslim and Islam in a 105 million word corpus of a large Swedish Internet forum from 2000 to 2013. Despite the increased importance of social media in the (re)production of discursive power in society, this is the first study of its kind. The analysis shows that Muslims are portrayed in the forum as a homogeneous outgroup that is embroiled in conflict, violence and extremism: characteristics that are described as emanating from Islam as a religion. These patterns are strikingly similar to – but often more extreme versions of – those previously found in analysis of traditional media. This indicates that, in this case, the internet forum seems to serve as an “online amplifier” that reflects and reinforces existing discourses in traditional media, which is likely to result in even stronger polarizing effects on public discourses.

115 citations

Journal ArticleDOI
TL;DR: A comprehensive literature review of 89 peer-reviewed journal articles reporting findings of empirical studies using conversation analysis methods to understand social interaction online shows that studies are using CA to understand “mundane” conversational contexts, as well as institutional talk from educational, counseling and workplace settings.
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.

95 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202320
202244
202157
202057
201956
201854