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Media Bias Characterization in Brazilian Presidential Elections

Published: 12 September 2019 Publication History

Abstract

News media bias is commonly associated with framing information so as to influence readers judgments. It is not rare to find different news outlets reporting the same events under different perspectives with the intention to deliberately influence the reader. For example, making one side's ideological perspective look better than another. This may be an indication of a well known cognitive bias, the framing effect, which states that people may change their judgment based on how the information is presented (or framed). According to a 2017's survey from the Knight Foundation and Gallup, Americans believe that 62% of the news they consume is biased [1]. Still according to the survey, there is a sharp divergence of bias perception across Republicans and Democrats regarding news organizations. This implies that the perception of bias may be affected by whether one agrees (or not) with the ideological leaning (when present) of the news source. How to expose such biases in an automatic fashion from textual content only? One way to do that is by comparing different news outlets on the same stories and look for divergences. In this talk, we present an investigation on news media bias in the context of Brazilian presidential elections by comparing four popular news outlets during three consecutive election years (2010, 2014, and 2018). We analyse the textual content of news stories in search for three kinds of bias: coverage, association, and subjective language. Coverage bias is related to differences in mention rates of candidates and parties. Association bias [2] occurs when, for example, one candidate is associated with a negative concept while another not. Subjective bias [3], has to do with wording that attempts to influence the readers by appealing to emotion, stereotypes, or persuasive language. We perform a thorough analysis on a large scale news data set where several such biases are exposed.

References

[1]
Perceived accuracy and bias in the news media. Retrieved from https://www.knightfoundation.org/reports/perceived-accuracy-and-bias-in-the-news-media
[2]
Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan. 2017. Semantics derived automatically from language corpora contain human-like biases. Science 356,6334 (April 2017), 183--186.
[3]
Evelin Amorim, Marcia Cançado, and Adriano Veloso. 2018. Automated Essay Scoring in the Presence of biased Ratings. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), Vol. 1. 229--237.

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  1. Media Bias Characterization in Brazilian Presidential Elections

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    cover image ACM Conferences
    SIdEWayS'19: Proceedings of the 5th International Workshop on Social Media World Sensors
    September 2019
    32 pages
    ISBN:9781450369039
    DOI:10.1145/3345645
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 12 September 2019

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    Author Tags

    1. brazilian presidential elections
    2. coverage
    3. media bias
    4. news outlets
    5. subjectivity
    6. textual content analysis
    7. word embedding association test

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    SIdEWayS'19 Paper Acceptance Rate 3 of 7 submissions, 43%;
    Overall Acceptance Rate 6 of 13 submissions, 46%

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