Decoding Political Polarization in Social Media Interactions
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866911944314716160 |
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| author | Pecile, Giulio Di Marco, Niccolò Cinelli, Matteo Quattrociocchi, Walter |
| author_facet | Pecile, Giulio Di Marco, Niccolò Cinelli, Matteo Quattrociocchi, Walter |
| contents | Social media platforms significantly influence ideological divisions by enabling users to select information that aligns with their beliefs and avoid opposing viewpoints. Analyzing approximately 47 million Facebook posts, this study investigates the interactions of around 170 million users with news pages, revealing distinct patterns based on political orientations. While users generally prefer content that reflects their political biases, the extent of engagement varies even among individuals with similar ideological leanings. Specifically, political biases heavily influence commenting behaviors, particularly among users leaning towards the center-left and the right. Conversely, the 'likes' from center-left and centrist users are more indicative of their political affiliations. This research illuminates the complex relationship between social media behavior and political polarization, offering new insights into the manifestation of ideological divisions online. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_03773 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Decoding Political Polarization in Social Media Interactions Pecile, Giulio Di Marco, Niccolò Cinelli, Matteo Quattrociocchi, Walter Social and Information Networks Physics and Society Social media platforms significantly influence ideological divisions by enabling users to select information that aligns with their beliefs and avoid opposing viewpoints. Analyzing approximately 47 million Facebook posts, this study investigates the interactions of around 170 million users with news pages, revealing distinct patterns based on political orientations. While users generally prefer content that reflects their political biases, the extent of engagement varies even among individuals with similar ideological leanings. Specifically, political biases heavily influence commenting behaviors, particularly among users leaning towards the center-left and the right. Conversely, the 'likes' from center-left and centrist users are more indicative of their political affiliations. This research illuminates the complex relationship between social media behavior and political polarization, offering new insights into the manifestation of ideological divisions online. |
| title | Decoding Political Polarization in Social Media Interactions |
| topic | Social and Information Networks Physics and Society |
| url | https://arxiv.org/abs/2407.03773 |