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Linking the Dynamics of User Stance to the Structure of Online Discussions

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Advances in Intelligent Data Analysis XIX (IDA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12695))

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Abstract

This paper studies the dynamics of opinion formation and polarization in social media. We investigate whether users’ stance concerning contentious subjects is influenced by the online discussions they are exposed to and interactions with users supporting different stances. We set up a series of predictive exercises based on machine learning models. Users are described using several posting activities features capturing their overall activity levels, posting success, the reactions their posts attract from users of different stances, and the types of discussions in which they engage. Given the user description at present, the purpose is to predict their stance in the future. Using a dataset of Brexit discussions on the Reddit platform, we show that the activity features regularly outperform the textual baseline, confirming the link between exposure to discussion and opinion. We find that the most informative features relate to the stance composition of the discussion in which users prefer to engage.

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Notes

  1. 1.

    Supplementary Information available online: https://arxiv.org/pdf/2101.09852.pdf#page=13.

  2. 2.

    Code and data publicly available: https://github.com/behavioral-ds/online-opinion-dynamics.

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Acknowledgement

This work was partially supported by IDEXLYON ACADEMICS Project ANR-16-IDEX-0005 of the French National Research Agency, Facebook Research under the Content Policy Research Initiative grants, and the Defence Science and Technology Group of the Australian Department of Defence. We thank Keneth Benoit, who generously shared the Twitter dataset of Brexit discussions [1].

Author information

Authors and Affiliations

  1. Univ Lyon, UJM -Saint -Etienne, CNRS, OGS, Saint-Etienne, France

    Christine Largeron & Andrei Mardale

  2. Data Science Institute, University of Technology Sydney, Sydney, Australia

    Marian-Andrei Rizoiu

Authors
  1. Christine Largeron
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  2. Andrei Mardale
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  3. Marian-Andrei Rizoiu
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Corresponding author

Correspondence to Marian-Andrei Rizoiu .

Editor information

Editors and Affiliations

  1. University of Coimbra, Coimbra, Portugal

    Pedro Henriques Abreu

  2. University of Porto, Porto, Portugal

    Pedro Pereira Rodrigues

  3. University of Granada, Granada, Spain

    Alberto Fernández

  4. University of Porto, Porto, Portugal

    João Gama

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Largeron, C., Mardale, A., Rizoiu, MA. (2021). Linking the Dynamics of User Stance to the Structure of Online Discussions. In: Abreu, P.H., Rodrigues, P.P., Fernández, A., Gama, J. (eds) Advances in Intelligent Data Analysis XIX. IDA 2021. Lecture Notes in Computer Science(), vol 12695. Springer, Cham. https://doi.org/10.1007/978-3-030-74251-5_22

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  • DOI: https://doi.org/10.1007/978-3-030-74251-5_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-74250-8

  • Online ISBN: 978-3-030-74251-5

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