Modelling the spillover from online engagement to offline protest: stochastic dynamics and mean-field approximations on networks
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866912490290413568 |
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| author | Tian, Moyi Brantingham, P. Jeffrey Rodríguez, Nancy |
| author_facet | Tian, Moyi Brantingham, P. Jeffrey Rodríguez, Nancy |
| contents | Social media is transforming various aspects of offline life, from everyday decisions such as dining choices to the progression of conflicts. In this study, we propose a coupled modelling framework with an online social network layer to analyse how engagement on a specific topic spills over into offline protest activities. We develop a stochastic model and derive several mean-field models of varying complexity. These models allow us to estimate the reproductive number and anticipate when surges in activity are likely to occur. A key factor is the transmission rate between the online and offline domains; for offline outbursts to emerge, this rate must fall within a critical range, neither too low nor too high. Additionally, using synthetic networks, we examine how network structure influences the accuracy of these approximations. Our findings indicate that low-density networks need more complex approximations, whereas simpler models can effectively represent higher-density networks. When tested on two real-world networks, however, increased complexity did not enhance accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_13310 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Modelling the spillover from online engagement to offline protest: stochastic dynamics and mean-field approximations on networks Tian, Moyi Brantingham, P. Jeffrey Rodríguez, Nancy Physics and Society Social and Information Networks Dynamical Systems Adaptation and Self-Organizing Systems Populations and Evolution Social media is transforming various aspects of offline life, from everyday decisions such as dining choices to the progression of conflicts. In this study, we propose a coupled modelling framework with an online social network layer to analyse how engagement on a specific topic spills over into offline protest activities. We develop a stochastic model and derive several mean-field models of varying complexity. These models allow us to estimate the reproductive number and anticipate when surges in activity are likely to occur. A key factor is the transmission rate between the online and offline domains; for offline outbursts to emerge, this rate must fall within a critical range, neither too low nor too high. Additionally, using synthetic networks, we examine how network structure influences the accuracy of these approximations. Our findings indicate that low-density networks need more complex approximations, whereas simpler models can effectively represent higher-density networks. When tested on two real-world networks, however, increased complexity did not enhance accuracy. |
| title | Modelling the spillover from online engagement to offline protest: stochastic dynamics and mean-field approximations on networks |
| topic | Physics and Society Social and Information Networks Dynamical Systems Adaptation and Self-Organizing Systems Populations and Evolution |
| url | https://arxiv.org/abs/2507.13310 |