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Identifying Similar Opinions in News Comments Using a Community Detection Algorithm

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Social Informatics (SocInfo 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9471))

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Abstract

Despite playing many important roles in society, the news media have been frequently criticised for failing to represent a wide range of viewpoints. Online news systems have the potential to allow readers to add additional information and perspectives. However, due to the simplicity of the filtering mechanisms typically employed, these systems can themselves be prone to over-promoting popular viewpoints at the expense of others. Previous research has attempted to diversify news comments through the use of content similarity, sentiment analysis, named entity recognition, and other factors. In this paper we propose the use of a commonly used community detection algorithm on a network of voting data to identify sentiment groups in news discussion threads, with the eventual goal that these groups may be used to present diverse content. In a controlled experiment with 154 participants, we verify that the Louvain Community Detection algorithm is able to group users with accuracy comparable to an average human. This produces groups containing users who share similar sentiment on a given topic. This is an important step towards ensuring that each group is represented, as by using this method future news systems can ensure that more diverse views are represented in open comment threads.

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Authors and Affiliations

  1. Web and Internet Science, School of Electronics and Computer Science, University of Southampton, Southampton, UK

    Jonathan Scott & David Millard

  2. Sociology, School of Social Sciences, University of Southampton, Southampton, UK

    Pauline Leonard

Authors
  1. Jonathan Scott
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  2. David Millard
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  3. Pauline Leonard
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Corresponding author

Correspondence to Jonathan Scott .

Editor information

Editors and Affiliations

  1. Microsoft Research Asia, Beijing, China

    Tie-Yan Liu

  2. Singapore Management University, Singapore, Singapore

    Christie Napa Scollon

  3. Tsinghua University, Beijing, China

    Wenwu Zhu

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Scott, J., Millard, D., Leonard, P. (2015). Identifying Similar Opinions in News Comments Using a Community Detection Algorithm. In: Liu, TY., Scollon, C., Zhu, W. (eds) Social Informatics. SocInfo 2015. Lecture Notes in Computer Science(), vol 9471. Springer, Cham. https://doi.org/10.1007/978-3-319-27433-1_7

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  • DOI: https://doi.org/10.1007/978-3-319-27433-1_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27432-4

  • Online ISBN: 978-3-319-27433-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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