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Crises of reputation as asynchronous online polylogues

Crises of reputation as asynchronous online polylogues AbstractCrises of reputation are rarely studied from the linguistic point of view, which results in several research gaps. Therefore, in this study three selected crisis cases have been analyzed as asynchronous online polylogues—Internet debates performed by stakeholders in different sources from the moment of publication. In this approach corpus analysis has been combined with the theory of computer-mediated communication, speech acts and a semantic study of emotions. One of the findings was that certain common patterns of subtopics, emotion expressions and communicative actions are noticeable in the user-generated content across different crisis cases. Contrary to some NLP studies, emotions expressed by stakeholders in a crisis situation refer not to the major topic, but to its subtopics, which impacts the construction of text-mining models. Unlike in pre-social media studies, sarcasm and not anger is the major emotion expressed textually in reaction to a crisis of reputation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Review of Pragmatics Brill

Crises of reputation as asynchronous online polylogues

International Review of Pragmatics , Volume 15 (1): 31 – Jan 19, 2023

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References (18)

Publisher
Brill
Copyright
Copyright © Koninklijke Brill NV, Leiden, The Netherlands
ISSN
1877-3095
eISSN
1877-3109
DOI
10.1163/18773109-01501006
Publisher site
See Article on Publisher Site

Abstract

AbstractCrises of reputation are rarely studied from the linguistic point of view, which results in several research gaps. Therefore, in this study three selected crisis cases have been analyzed as asynchronous online polylogues—Internet debates performed by stakeholders in different sources from the moment of publication. In this approach corpus analysis has been combined with the theory of computer-mediated communication, speech acts and a semantic study of emotions. One of the findings was that certain common patterns of subtopics, emotion expressions and communicative actions are noticeable in the user-generated content across different crisis cases. Contrary to some NLP studies, emotions expressed by stakeholders in a crisis situation refer not to the major topic, but to its subtopics, which impacts the construction of text-mining models. Unlike in pre-social media studies, sarcasm and not anger is the major emotion expressed textually in reaction to a crisis of reputation.

Journal

International Review of PragmaticsBrill

Published: Jan 19, 2023

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