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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| Online-Zugang: | https://arxiv.org/abs/2305.16855 |
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| _version_ | 1866913693474750464 |
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| author | Deffuant, Guillaume Keijzer, Marijn A. Banisch, Sven |
| author_facet | Deffuant, Guillaume Keijzer, Marijn A. Banisch, Sven |
| contents | We live in an age of information abundance but know little about how this influences our opinions or attitudes. A common expectation is that people consulting numerous pieces of information, well balancing the different sides of an issue, will adopt a moderate attitude about the issue. We claim that this expectation is deceitful and suggest that people tend to get extreme and dogmatic about an issue when they consult abundant unbiased information. The cause for this extremization is a hardening confirmation bias -- when their attitude gets more extreme, people get more likely to ignore information that differs from their views. Our claim is based on simulations of two fundamentally different computational models: a Bounded Confidence model and an empirically calibrated Persuasive Argument model. For both models, the attitude tends to be extreme when the computational agent consults abundant unbiased information. We analyze the extremization pathways displayed in the models and discuss how our results may affect views on polarization, and on the role of online media. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_16855 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | How opinions get more extreme in an age of information abundance Deffuant, Guillaume Keijzer, Marijn A. Banisch, Sven Physics and Society Multiagent Systems We live in an age of information abundance but know little about how this influences our opinions or attitudes. A common expectation is that people consulting numerous pieces of information, well balancing the different sides of an issue, will adopt a moderate attitude about the issue. We claim that this expectation is deceitful and suggest that people tend to get extreme and dogmatic about an issue when they consult abundant unbiased information. The cause for this extremization is a hardening confirmation bias -- when their attitude gets more extreme, people get more likely to ignore information that differs from their views. Our claim is based on simulations of two fundamentally different computational models: a Bounded Confidence model and an empirically calibrated Persuasive Argument model. For both models, the attitude tends to be extreme when the computational agent consults abundant unbiased information. We analyze the extremization pathways displayed in the models and discuss how our results may affect views on polarization, and on the role of online media. |
| title | How opinions get more extreme in an age of information abundance |
| topic | Physics and Society Multiagent Systems |
| url | https://arxiv.org/abs/2305.16855 |