Multi-opinion based method for quantifying polarization on social networks

Maneet Singh (), S. R. S. Iyengar () and Rishemjit Kaur ()
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Maneet Singh: Indian Institute of Technology Ropar
S. R. S. Iyengar: Indian Institute of Technology Ropar
Rishemjit Kaur: CSIR-Central Scientific Instruments Organization

Journal of Computational Social Science, 2025, vol. 8, issue 3, No 21, 17 pages

Abstract: Abstract Social media platforms have emerged as a hub for political and social interactions, and analyzing the polarization of opinions has been gaining attention. In this study, we have proposed a measure to quantify polarization on social networks. The proposed metric, unlike state-of-the-art methods, does not assume a two-opinion case and applies to multiple opinions. We tested our metric on different networks with a multi-opinion scenario and varying degrees of polarization. The scores obtained from the proposed metric were comparable to state-of-the-art methods on binary opinion-based benchmark networks. The technique also differentiated among networks with different levels of polarization in a multi-opinion scenario. We also quantified polarization in a retweet network obtained from Twitter regarding the usage of drugs like hydroxychloroquine or chloroquine in treating COVID-19. Our metric indicated a high level of polarized opinions among the users. These findings suggest uncertainty among users in the benefits of using hydroxychloroquine and chloroquine drugs to treat COVID-19 patients.

Keywords: Multi-opinion; Polarization; Hydroxychloroquine; COVID-19; Twitter; Social network (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s42001-025-00400-z

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