Determining citizens’ opinions about stories in the news media: analysing Google, Facebook and Twitter

Wandhöfer, Timo; Taylor, Steve; Walland, Paul; Geana, Ruxandra; Weichselbaum, Robert; Fernandez, Miriam and Sizov, Sergej (2012). Determining citizens’ opinions about stories in the news media: analysing Google, Facebook and Twitter. eJournal of eDemocracy & Open Government (JeDEM), 4(2) pp. 198–221.

URL: http://www.jedem.org/article/view/141

Abstract

We describe a method whereby a governmental policy maker can discover citizens’ reaction to news stories. This is particularly relevant in the political world, where governments’ policy statements are reported by the news media and discussed by citizens. The work here addresses two main questions: whereabouts are citizens discussing a news story, and what are they saying? Our strategy to answer the first question is to find news articles pertaining to the policy statements, then perform internet searches for references to the news articles’ headlines and URLs. We have created a software tool that schedules repeating Google searches for the news articles and collects the results in a database, enabling the user to aggregate and analyse them to produce ranked tables of sites that reference the news articles. Using data mining techniques we can analyse data so that resultant ranking reflects an overall aggregate score, taking into account multiple datasets, and this shows the most relevant places on the internet where the story is discussed. To answer the second question, we introduce the WeGov toolbox as a tool for analysing citizens’ comments and behaviour pertaining to news stories. We first use the tool for identifying social network discussions, using different strategies for Facebook and Twitter. We apply different analysis components to analyse the data to distil the essence of the social network users’ comments, to determine influential users and identify important comments.

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About

  • Item ORO ID
  • 36768
  • Item Type
  • Journal Item
  • ISSN
  • 2075-9517
  • Project Funding Details
  • Funded Project NameProject IDFunding Body
    Not Set248512European Commission
  • Extra Information
  • This issue presents updated and extended papers from the CEDEM11 and CEDEM12 (Conference on eDemocracy and Open Government held in 2011 and 2012) based on the best reviewer scores as well as extended versions of some keynotes' papers.

    The WeGov project (no. 248512) is funded with support from the European Commission under the SEVENTH FRAMEWORK PROGRAMME THEME ICT 2009.7.3 ICT for Governance and Policy Modelling.
  • Keywords
  • e-participation; e-government; social networks; news articles, news stories; political engagement; citizens’ opinions; dialogue; Facebook; Twitter
  • Academic Unit or School
  • Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
    Faculty of Science, Technology, Engineering and Mathematics (STEM)
  • Research Group
  • Centre for Research in Computing (CRC)
  • Copyright Holders
  • © 2012 The Authors
  • Depositing User
  • Kay Dave

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