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Measuring Media Partisanship during Election: The Case of 2019 Indonesia Election

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  • Maulana, Ardian
  • Situngkir, Hokky

Abstract

Analysis of media partisanship during election requires an objective measurement of political bias that frames the content of information conveyed to the audience. In this study we propose a method for political stance detection of online news outlets based on the behavior of their audience in social media. The method consists of 3 processing stages, namely hashtag-based user labeling, network-based user labeling and media classification. We applied this methodology to the tweet dataset related to the 2019 Indonesian general election, to observed media alignments during the election. Evaluation results show that the proposed method is very effective in detecting the political affiliation of twitter users as well as predicting the political stance of news media. Over all, the stance of media in the spectrum of political valence confirms the general allegations of media partisanship during 2019 Indonesian election. Further elaboration regarding news consumption behavior shows that low-credibility news outlets tend to have extreme political positions, while partisan readers tend not to question the credibility of the news sources they share.

Suggested Citation

  • Maulana, Ardian & Situngkir, Hokky, 2020. "Measuring Media Partisanship during Election: The Case of 2019 Indonesia Election," MPRA Paper 101950, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:101950
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    References listed on IDEAS

    as
    1. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    2. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    3. Carolina Becatti & Guido Caldarelli & Renaud Lambiotte & Fabio Saracco, 2019. "Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-16, December.
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    More about this item

    Keywords

    news media network; label propagation algorithm; twitter; election; media partisanship; news consumption;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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