Abstract
Kennedy discusses action research with city-based, public sector organisations, which attempted to experiment with these methods, evaluate their potential use and reflect on their normative consequences. She argues that it is difficult to discuss the problems of data mining openly with public sector actors because doing social media data mining is motivated by a will to produce results, or a ‘desire for numbers’—this concept brings together Porter’s discussion of trust in numbers (Trust in numbers: The pursuit of objectivity in science and public life. Princeton, NJ: Princeton University Press, 1996) with Grosser’s (Computational Culture: A Journal of Software Studies, 4, 2014) work on the ways in which the metrification of sociality on social media platforms creates a desire for more and more metrics. Nonetheless, public sector social media data mining aspires to enhance understanding of public opinion and inclusion in public processes and so aims to serve the public good. Kennedy argues that it is therefore ‘empirically inaccurate’ (Banks, The politics of cultural work. Basingstoke, England: Palgrave Macmillan, 2007) to understand public sector data mining in only negative terms.
Keywords
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anderson, C. (2008). The end of theory: Will the data deluge make the scientific method obsolete? Edge. Available at: http://www.edge.org/3rd_culture/anderson08/anderson08_index.html. Accessed 7 May 2010.
Anstead, N., & O’Loughlin, B. (2014). Social media analysis and public opinion: The 2010 UK general election. Journal of Computer-Mediated Communication, 20(2), 204–220.
Banks, M. (2007). The politics of cultural work. Basingstoke, England: Palgrave Macmillan.
Barnes, M., Newman, J., & Sullivan, H. C. (2007). Power, participation and political renewal: Case studies in public participation. Bristol: Policy Press.
Baym, N. (2013). Data not seen: The uses and shortcomings of social media metrics, First Monday, 18(10). Available at: http://firstmonday.org/ojs/index.php/fm/article/view/4873/3752. Accessed 11 Feb 2014.
Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological and scholarly phenomenon. Information, Communication and Society, 15(5), 662–679.
Bucher, T. (2012). Want to be on the top? Algorithmic power and the threat of invisibility on Facebook. New Media & Society, 14(7), 1164–1180.
Coleman, S., Firmstone, J., Kennedy, H., Moss, G., Parry, K., Thornham, H., Thumim, N. (2012). Public engagement and cultures of expertise, RCUK Digital Economy Communities and Cultures Network + Scoping Report. Available at: http://www.communitiesandculture.org/files/2013/01/Scoping-report-Leeds-and-Suggestions.pdf. Accessed 1 Feb 2013.
Crawford, K. (2013). The hidden biases of big data, Harvard Business Review, 1 April. Online: http://blogs.hbr.org/cs/2013/04/the_hidden_biases_in_big_data.html. Accessed 6 Jan 2014.
Cruikshank, B. (2000). The will to empower: Democratic citizens and other subjects. Ithaca, NY: Cornell University Press.
Ding, Y., Du, Y., Hu, Y., Liu, Z., Wang, L., Ross, K.W., & Ghose, A. (2011). Broadcast yourself: Understanding YouTube uploaders. Paper presented at the Internet Measurement Conference, IMC’11, 2–4 November, Berlin. Available at: http://conferences.sigcomm.org/imc/2011/program.htm. Accessed 7 May 2014.
Feenberg, A. (1999). Questioning technology. London: Routledge.
Freire, P. (1970). Pedagogy of the Oppressed. New York: Continuum.
Gillespie, T. (2014). The relevance of algorithms. In T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Media technologies: Essays on communication, materiality, and society. Cambridge, MA: MIT Press. Available at: http://www.tarletongillespie.org/essays/Gillespie%20-%20The%20Relevance%20of%20Algorithms.pdf. Accessed 12 Jan 2015.
Graham, M., Hale, S. A., & Gaffney, D. (2013). Where in the world are you? Geolocation and language identification in Twitter. Professional Geographer. Available at: http://arxiv.org/ftp/arxiv/papers/1308/1308.0683.pdf. Accessed 12th May 2014.
Graham, T., & Wright, S. (2014). Discursive equality and everyday talk online: The impact of “superparticipants”. Journal of Computer-Mediated Communication, 19, 625–642.
Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91(3), 481–510.
Grosser, B. (2014). What do metrics want? How quantification prescribes social interaction on Facebook. Computational Culture: A Journal of Software Studies, 4. Available at: http://computationalculture.net/article/what-do-metrics-want. Accessed 10 Jan 2015.
Hammersley, M. (2002). Action research: A contradiction in terms? British Educational Research Association. Exeter, England, 12-14 September 2002. Available at: http://www.leeds.ac.uk/educol/documents/00002130.htm. Accessed 12 May 2014.
Helmond, A., & Gerlitz, C. (2013). The like economy: Social buttons and the data-intensive web. New Media and Society, 15(8), 1348–1365.
Horkheimer, M., & Adorno, T. (1948). Dialectic of enlightenment. Frankfurt, Germany: Fischer.
Huff, D. (1954). How to lie with statistics. London: Penguin.
Kennedy, H., Elgesem, D., & Miguel, C. (2015). On fairness: User perspectives on social media data mining. Convergence (forthcoming).
Kennedy, H., Hill, R., Allen, W., & Kirk, A. (2016). Engaging with data visualisations: Users, socio-cultural factors and definitions of effectiveness. Information Visualisation (forthcoming).
Kennedy, H., & Moss, G. (2015). Known or knowing publics? Social media data mining and the question of public agency. Big Data and Society (forthcoming).
Kennedy, H. (2015) ‘Seeing Data’, LSE Impact Blog. Retrieved July 22, 2015, from http://blogs.lse.ac.uk/impactofsocialsciences/2015/07/22/seeing-data-how-people-engage-with-data-visualisations/.
Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter, a social network or a news media? Proceedings of the 19th International World Wide Web (WWW) Conference, April 26–30, Raleigh NC, 591–600. Available at http://an.kaist.ac.kr/traces/WWW2010.html l. Accessed 28 Apr 2014.
Law, J., Ruppert, E., & Savage, M. (2011). The double social life of methods. CRESC Working Paper, 95. Available at: http://www.open.ac.uk/researchprojects/iccm/library/164. Accessed 4th June 2012.
Law, J., & Urry, J. (2004). Enacting the social. Economy and Society, 33(3), 390–410.
Lowndes, V., & Squires, S. (2012). Cuts, collaboration and creativity. Public Money & Management, 32, 401–408.
Manovich, L. (2011). Trending: The promises and the challenges of big social data. Available at: http://www.manovich.net/DOCS/Manovich_trending_paper.pdf. (Also in M. K. Gold (ed) Debates in the Digital Humanities). Accessed 9 Oct 2013.
Marres, N., & Gerlitz, C. (2015). Interface methods: Renegotiating relations between digital social research, STS and sociology. Sociological Review (forthcoming).
McCarthy, A. (2008). From the ordinary to the concrete: Cultural studies and the politics of scale. In M. White & J. Schwoch (Eds.), Questions of method in cultural studies. Oxford, England: Wiley Blackwell.
Moss, G., Kennedy, H., Moshonas, S., & Birchall, C. (2015). Knowing your publics: The use of social media analytics in local government. Journal of Information Technology and Polity, (forthcoming).
Perlin, R. (2011). Intern nation: How to earn nothing and learn little in the brave new economy. London: Verso Books.
Peters, J. D. (1995). Historical tensions in the concept of public opinion. In T. L. Glasser & C. T. Salmon (Eds.), Public opinion and the communication of consent. New York: Guilford Press.
Polsky, N. (1971). Hustlers, beats, and others. Pscataway, NJ: Aldine.
Porter, T. M. (1995). Trust in numbers: the pursuit of objectivity in science and public life.. Princeton: Princeton University Press.
Porter, T. M. (1996). Trust in numbers: The pursuit of objectivity in science and public life. Princeton, NJ: Princeton University Press.
Ravetz, J.R. (1996). In numbers we trust. Issues in Science and Technology. Available at: http://www.issues.org/13.2/ravetz.htm. Accessed 12 July 2015.
Reason, P., & Bradbury, H. (2001). Introduction. In P. Reason & H. Bradbury (Eds.), Handbook of action research: Participative inquiry and practice. London: Sage.
Roginsky, S. (2014). Research Seminar, Institute of Communications Studies, University of Leeds, 6 May 2014.
van Dijck, J. (2013b). You have one identity: Performing the self on Facebook and LinkedIn. Media, Culture & Society, 35(2), 199–215.
van Dijck, J. (2014). Datafication, dataism and dataveillance: Big data between scientific paradigm and ideology. Surveillance and Society, 12(2), 197–208.
Author information
Authors and Affiliations
Copyright information
© 2016 The Editor(s) (if applicable) and The Author(s)
About this chapter
Cite this chapter
Kennedy, H. (2016). Public Sector Experiments with Social Media Data Mining. In: Post, Mine, Repeat. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-35398-6_4
Download citation
DOI: https://doi.org/10.1057/978-1-137-35398-6_4
Published:
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-137-35397-9
Online ISBN: 978-1-137-35398-6
eBook Packages: Literature, Cultural and Media StudiesLiterature, Cultural and Media Studies (R0)