Quantifying Polarization: A Comparative Study of Measures and Methods
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866916564843888640 |
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| author | Di Martino, Edoardo Cinelli, Matteo Cerqueti, Roy Quattrociocchi, Walter |
| author_facet | Di Martino, Edoardo Cinelli, Matteo Cerqueti, Roy Quattrociocchi, Walter |
| contents | Political polarization, a key driver of social fragmentation, has drawn increasing attention for its role in shaping online and offline discourse. Despite significant efforts, accurately measuring polarization within ideological distributions remains a challenge. This study evaluates five widely used polarization measures, testing their strengths and weaknesses with synthetic datasets and a real-world case study on YouTube discussions during the 2020 U.S. Presidential Election. Building on these findings, we present a novel adaptation of Kleinberg's burst detection algorithm to improve mode detection in polarized distributions. By offering both a critical review and an innovative methodological tool, this work advances the analysis of ideological patterns in social media discourse. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_07473 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Quantifying Polarization: A Comparative Study of Measures and Methods Di Martino, Edoardo Cinelli, Matteo Cerqueti, Roy Quattrociocchi, Walter Computers and Society Social and Information Networks Physics and Society Political polarization, a key driver of social fragmentation, has drawn increasing attention for its role in shaping online and offline discourse. Despite significant efforts, accurately measuring polarization within ideological distributions remains a challenge. This study evaluates five widely used polarization measures, testing their strengths and weaknesses with synthetic datasets and a real-world case study on YouTube discussions during the 2020 U.S. Presidential Election. Building on these findings, we present a novel adaptation of Kleinberg's burst detection algorithm to improve mode detection in polarized distributions. By offering both a critical review and an innovative methodological tool, this work advances the analysis of ideological patterns in social media discourse. |
| title | Quantifying Polarization: A Comparative Study of Measures and Methods |
| topic | Computers and Society Social and Information Networks Physics and Society |
| url | https://arxiv.org/abs/2501.07473 |