I tiakina i:
| Ngā kaituhi matua: | , , , , |
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| Hōputu: | Preprint |
| I whakaputaina: |
2024
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| Ngā marau: | |
| Urunga tuihono: | https://arxiv.org/abs/2411.19829 |
| Ngā Tūtohu: |
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| _version_ | 1866917961723281408 |
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| author | Sevinchan, Yunus Sarkanych, Petro Tenenbaum, Abi Holovatch, Yurij Romanczuk, Pawel |
| author_facet | Sevinchan, Yunus Sarkanych, Petro Tenenbaum, Abi Holovatch, Yurij Romanczuk, Pawel |
| contents | The ability of groups to make accurate collective decisions depends on a complex interplay of various factors, such as prior information, biases, social influence, and the structure of the interaction network. Here, we investigate a spin model that accounts for heterogeneous preferences and enables control over the non-linearity of social interactions. Building on previous results for complete graphs and regular 2D lattices, we investigate how the modification of network topology towards (sparse) random graphs can affect collective decision-making. We use two different measures of susceptibility to assess the responsiveness of the system to internal and external perturbations. In particular, we investigate how the maximum of susceptibility depends on network connectivity. Based on our findings, we discuss how collective systems might adapt to changes in environmental fluctuations by adjusting their network structure or the nature of their social interactions in order to remain in the region of maximal susceptibility. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_19829 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Collective decision-making with heterogeneous biases: Role of network topology and susceptibility Sevinchan, Yunus Sarkanych, Petro Tenenbaum, Abi Holovatch, Yurij Romanczuk, Pawel Physics and Society Statistical Mechanics Adaptation and Self-Organizing Systems The ability of groups to make accurate collective decisions depends on a complex interplay of various factors, such as prior information, biases, social influence, and the structure of the interaction network. Here, we investigate a spin model that accounts for heterogeneous preferences and enables control over the non-linearity of social interactions. Building on previous results for complete graphs and regular 2D lattices, we investigate how the modification of network topology towards (sparse) random graphs can affect collective decision-making. We use two different measures of susceptibility to assess the responsiveness of the system to internal and external perturbations. In particular, we investigate how the maximum of susceptibility depends on network connectivity. Based on our findings, we discuss how collective systems might adapt to changes in environmental fluctuations by adjusting their network structure or the nature of their social interactions in order to remain in the region of maximal susceptibility. |
| title | Collective decision-making with heterogeneous biases: Role of network topology and susceptibility |
| topic | Physics and Society Statistical Mechanics Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2411.19829 |