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Who Benefits When Discourse Gets Democratised? Analysing a Twitter Corpus around the British Benefits Street Debate

  • Paul Baker
  • Tony McEnery
Part of the Palgrave Advances in Language and Linguistics book series (PADLL)

Abstract

In this chapter we examine discourses on the social media site Twitter around people who receive government support (commonly referred to as benefits), in the UK. Between 2008–2009 and 2011–2012, the UK experienced recession, and after coming to power in 2010 the Conservative-led coalition government embarked on a program of fiscal austerity that included cuts to some benefits. Baker (forthcoming) analysed the discourse around benefits in Britain’s most widely-read newspaper The Sun (a conservative tabloid), comparing the years 2002 and 2012. In 2012, the discourse around benefits was less sympathetic towards many types of benefit recipients, with the newspaper notably focusing on two constructions: benefits cheats and benefits culture, which respectively resulted in negative stories at the level of both the individual and the wider society. The newspaper painted a compelling picture of a benefits system created by the previous government that was both too soft and open to abuse and thus in need of reform.

Keywords

Lottery Ticket Newspaper Corpus Taboo Word Location Base Social Network Benefit Claimant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Anderson, B. (1983) Imagined Communities: Reflections on the Origin and Spread of Nationalism ( London: Verso).Google Scholar
  2. Anthony, Laurence. (2011) AntConc (Version 3.2.2) [Computer Software]. Tokyo, Japan: Waseda University. Available at: http://www.antlab.sci.waseda.ac.jp/.Google Scholar
  3. Baker, P. (forthcoming) ‘Making the needy look greedy: Using corpus methods to examine The Sun’s discourse around benefits’, in J. Rahilly and V. Vander (eds.) Crossing Boundaries: Interdisciplinarity in Language Studies (Amsterdam: John Benjamins).Google Scholar
  4. Baker, P., Gabrielatos, C. and McEnery, T. (2013) Discourse Analysis and Media Attitudes: The Representation of Islam in the British Press ( Cambridge: Cambridge University Press).CrossRefGoogle Scholar
  5. Bossy, J. (2002) ‘Moral arithmetic: Seven sins into Ten Commandments’, in E. Leites (ed.) Conscience and Casuistry in Early Modern Europe ( Cambridge: Cambridge University Press ), pp. 214–23.Google Scholar
  6. Burr, V. (1995) An Introduction to Social Constructionism ( London: Routledge).CrossRefGoogle Scholar
  7. Brezina, V., McEnery, T. and Wattam, S. (2015) ‘Collocations in context: A new perspective on collocational networks’, International Journal of Corpus Linguistics, 20 (2).Google Scholar
  8. Dubé, L., Bourhis, A. and Jacob, R. (2005) ‘The impact of structuring characteristics on the launching of virtual communities of practice’, Journal of Organizational Change Management, 18 (2): 145–66.CrossRefGoogle Scholar
  9. Foucault, M. (1972) The Archaeology of Knowledge ( London: Tavistock).Google Scholar
  10. Jane, E. A. (2014) ‘Beyond antifandom: Cheerleading textual hate and new media ethics’, International Journal of Cultural Studies, 17 (2): 175–90.CrossRefGoogle Scholar
  11. Katz, M. B. (2013) The Undeserving Poor: America’s Enduring Confrontation with Poverty. Second Edition ( New York: Oxford University Press).Google Scholar
  12. Kendall, D. (2005) Framing Class: Media Representations of Wealth and Poverty in America ( Rowmand & Littlefield: Lanham MD).Google Scholar
  13. Laboreiro, G., Sarmento, L., Teixeira, J. and Oliveira, E. (2010) ‘Tokenizing microblogging messages using a text classification approach’, in Proceedings of the Fourth Workshop on Analytics for Noisy Unstructured Text Data. Toronto: ACM.Google Scholar
  14. Le Bon, G. (1896) The Crowd: A Study of the Popular Mind ( New York: The Macmillan Co.).Google Scholar
  15. McIntosh, M. K. (2005) ‘Poverty, charity, and coercion in Elizabethan England’, Journal of Interdisciplinary History, 35 (3): 457–79.CrossRefGoogle Scholar
  16. Merton, R. K. (1968) ‘The Matthew effect in science’, Science, 159 (3810): 56–63.CrossRefGoogle Scholar
  17. Nystrand, M. (1982) What Writers Know: The Language, Process, and Structure of Written Discourse ( New York: Academic).Google Scholar
  18. OUP Dictionary Team (2009) RT This: OUP Dictionary Team Monitors Twitterer’s Tweets. Available at: http://blog.oup.com/2009/06/oxford-twitter/Google Scholar
  19. Rank, M. R., Yoon, H.-S. and Hirschl, T. A. (2003) ‘American poverty as a structural failing: Evidence and arguments’, Journal of Sociology and Social Welfare, 30 (4): 3–29.Google Scholar
  20. Schlieder, C. and Yanenko, O. (2010) ‘Spatio-temporal proximity and social distance: A confirmation framework for social reporting’, in Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks. San Jose, CA: ACM.Google Scholar
  21. Strauss, C. (2012) Making Sense of Public Opinion: American Discourses About Immigration and Social Problems ( Cambridge: Cambridge University Press).CrossRefGoogle Scholar
  22. Swales, J. M. (1990) Genre Analysis: English in Academic and Research Settings ( Cambridge: Cambridge University Press).Google Scholar
  23. Twitter Inc (2014) Prospectus. Available at: http://www.sec.gov/Archives/edgar/data/1418091/000119312513390321/d5 64001 ds 1. htm#toc.Google Scholar
  24. Zappavigna, M. (2012) Discourse of Twitter and Social Media ( London: Bloomsbury).Google Scholar
  25. Zhang, W., Johnson, T. J., Seltzer, T. and Bichard, S. L. (2010) ‘The revolution will be networked’, Social Science Computer Review, 28 (1): 75–92.CrossRefGoogle Scholar

Copyright information

© Paul Baker and Tony McEnery 2015

Authors and Affiliations

  • Paul Baker
  • Tony McEnery

There are no affiliations available

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