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Polarization in social media

Author

Listed:
  • Zhang, Congli
  • Wang, Xiaolei
  • Min, Yong
  • Yu, Shanqing
  • Wu, Ye
  • Xuan, Qi
  • Fu, Chenbo

Abstract

The development of social media has changed the way in which information is consumed by the public. However, it also promotes polarization, especially among the more controversial topics. Furthermore, recommendation systems commonly used in social media have been shown to emerge an echo chamber effect, amplifying user groups’ polarization. Most of current studies focus on analyzing the generation of polarization phenomena on social media but rarely investigate how to quantify polarization. In this study, we construct user opinion networks and utilize random walk to quantify the polarization of related topics. The experiments on three real datasets, i.e., Bilibili, YouTube and Reddit, demonstrate that there is polarization in Bilibili and YouTube, especially in Bilibili. Our work complements quantitative measurements of polarization in social media platforms.

Suggested Citation

  • Zhang, Congli & Wang, Xiaolei & Min, Yong & Yu, Shanqing & Wu, Ye & Xuan, Qi & Fu, Chenbo, 2025. "Polarization in social media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 665(C).
    • Handle: RePEc:eee:phsmap:v:665:y:2025:i:c:s0378437125001396
    DOI: 10.1016/j.physa.2025.130487
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    References listed on IDEAS

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    1. Sandro Sousa & Vincenzo Nicosia, 2022. "Quantifying ethnic segregation in cities through random walks," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
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    3. Christopher K. Tokita & Andrew M. Guess & Corina E. Tarnita, 2021. "Polarized information ecosystems can reorganize social networks via information cascades," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(50), pages 2102147118-, December.
    4. MARTIN, GREGORY J. & McCRAIN, JOSHUA, 2019. "Local News and National Politics," American Political Science Review, Cambridge University Press, vol. 113(2), pages 372-384, May.
    5. Max Falkenberg & Alessandro Galeazzi & Maddalena Torricelli & Niccolò Di Marco & Francesca Larosa & Madalina Sas & Amin Mekacher & Warren Pearce & Fabiana Zollo & Walter Quattrociocchi & Andrea Baronc, 2022. "Growing polarization around climate change on social media," Nature Climate Change, Nature, vol. 12(12), pages 1114-1121, December.
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    Cited by:

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    2. Maryam Arif & Soban Saeed, 2025. "Machine Learning Predictive Analytics for Social Media Enabled Women's Economic Empowerment in Pakistan," Papers 2512.12685, arXiv.org.

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