Harvey, Rosie
2020.
Twitter reactions to the UN’s #HeForShe campaign for gender equality: A corpus-based discourse analysis.
Journal of Corpora and Discourse Studies
3
, pp. 31-50.
10.18573/jcads.12
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Abstract
Previous research has shown that completing a corpus-based analysis of Twitter data presents several methodological challenges (McEnery et al., 2015; Zappavinga, 2012). This paper exemplifies one possible approach: analysing keywords to identify discourses. Twitter presents difficulties not only to corpus-based discourse analysists; researchers have argued that many not-for-profit organisations struggle to maximise the potential of social media sites such as Twitter (Lovejoy et al., 2012). This paper therefore analyses a corpus of tweets which contain the hashtag #HeForShe and were posted between 20th September 2014 and 2nd October 2014 inclusive. The main aim is to consider what discourses reveal about public opinion of the United Nation's HeForShe campaign for gender equality, immediately after the campaign launch. The analysis reveals that discussion of the campaign is largely positive; however, it is possible to identify unexploited opportunities, that is, ways that the campaign could have utilised Twitter to increase public engagement. This paper therefore makes several recommendations that future similar campaigns by not-for-profit organisations should ideally be aware of, in order to exploit these opportunities where possible. The analysis of discourses also enables a more general discussion of how concepts such as gender and feminism are portrayed in the corpus.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | English, Communication and Philosophy |
Subjects: | H Social Sciences > HM Sociology H Social Sciences > HQ The family. Marriage. Woman P Language and Literature > P Philology. Linguistics Q Science > QA Mathematics > QA76 Computer software |
Publisher: | Cardiff University Press |
ISSN: | 2515-0251 |
Date of First Compliant Deposit: | 2 July 2020 |
Date of Acceptance: | 30 August 2018 |
Last Modified: | 04 May 2023 00:34 |
URI: | https://orca.cardiff.ac.uk/id/eprint/137882 |
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