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An opinion diffusion model with clustered early adopters

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  • Deng, Lei
  • Liu, Yun
  • Xiong, Fei

Abstract

We propose an opinion dynamic model which studies the adoption process of new opinions or ideas by agents. The proposed model allows the observation range of an agent to be expanded in square lattices. The agent’s opinion update process is not only influenced by a neighbor’s choice but also by the whole environment that can be observed. The model shows a different result with the normal CODA model: if adopters’ initial opinions equal 0.6 and individual observation probability α equals 0.65, then diffusions with clustered early adopters are 3% faster than those with randomly scattered ones. Introducing the bounded confidence concept into our model leads to appearance of freezing effect in opinion dynamics.

Suggested Citation

  • Deng, Lei & Liu, Yun & Xiong, Fei, 2013. "An opinion diffusion model with clustered early adopters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3546-3554.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:17:p:3546-3554
    DOI: 10.1016/j.physa.2013.03.058
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Luo, Gui-Xun & Liu, Yun & Zeng, Qing-An & Diao, Su-Meng & Xiong, Fei, 2014. "A dynamic evolution model of human opinion as affected by advertising," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 254-262.
    2. Cheng, Zhichao & Xiong, Yang & Xu, Yiwen, 2016. "An opinion diffusion model with decision-making groups: The influence of the opinion’s acceptability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 429-438.
    3. Peres, Renana, 2014. "The impact of network characteristics on the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 330-343.
    4. Diao, Su-Meng & Liu, Yun & Zeng, Qing-An & Luo, Gui-Xun & Xiong, Fei, 2014. "A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 220-228.
    5. Fan, Kangqi & Pedrycz, Witold, 2016. "Opinion evolution influenced by informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 431-441.
    6. Fan, Kangqi & Pedrycz, Witold, 2015. "Emergence and spread of extremist opinions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 87-97.
    7. Meng, Yanhong & Yi, Yunhui & Xiong, Fei & Pei, Changxing, 2019. "T×oneHop approach for dynamic influence maximization problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 575-586.
    8. Huang, Chuanchao & Hu, Bin & Jiang, Guoyin & Yang, Ruixian, 2016. "Modeling of agent-based complex network under cyber-violence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 399-411.

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