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Dynamics of Deffuant Model in Activity-Driven Online Social Network

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Knowledge and Systems Sciences (KSS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 949))

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Abstract

In many social system the interactions among the individuals are rapidly changing and are characterized with timing. The dynamics of social interaction constantly affects the development of their opinions. However, most of the opinion evolution models characterize interpersonal opinion in static, structural properties of the network such as degree, cluster and distance. In this paper, an Deffuant opinion model based on the activity-driven network is developed to examine how different activity distribution effects the dynamics of opinion evolution. When the activity distribution complies with power-law distribution or random distribution, phase transition transform from polarization to consensus when threshold is 0.6 and 0.4, respectively. In the process of opinion formation the distribution of opinion clusters’ scales are complying with power-law distribution. Especially, under the power-law distribution the opinion disparity of the two clusters in polarization state is lower than the others, which means that the burst of the activity helps the individuals converging in opinion clusters in values. Finally we show that the speed to reach stable is influenced by the type of activity distribution. The simulation on power-distribution and random distribution need more time steps to get steady state.

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Funding

This work was supported in part by the National Natural Science Foundation (grant numbers 71401024, 71371040 and 71801145).

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Authors and Affiliations

  1. Dalian University of Technology, Dalian, 116024, Liaoning, China

    Jun Zhang & Haoxiang Xia

  2. Shandong University of Technology, Zibo, 255000, Shandong, China

    Jun Zhang & Peng Li

Authors
  1. Jun Zhang
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  2. Haoxiang Xia
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  3. Peng Li
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Corresponding authors

Correspondence to Jun Zhang or Haoxiang Xia .

Editor information

Editors and Affiliations

  1. School of Economics and Management, Tsinghua University, Beijing, China

    Jian Chen

  2. Graduate School of Business Sciences, University of Tsukuba, Bunkyō, Tokyo, Tokyo, Japan

    Yuji Yamada

  3. Faculty of Business Sciences, University of Tsukuba, Tokyo, Japan

    Mina Ryoke

  4. Institute of Systems Science, CAS Academy of Mathematics and Systems Sciences, Beijing, China

    Xijin Tang

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Zhang, J., Xia, H., Li, P. (2018). Dynamics of Deffuant Model in Activity-Driven Online Social Network. In: Chen, J., Yamada, Y., Ryoke, M., Tang, X. (eds) Knowledge and Systems Sciences. KSS 2018. Communications in Computer and Information Science, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-3149-7_16

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  • DOI: https://doi.org/10.1007/978-981-13-3149-7_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3148-0

  • Online ISBN: 978-981-13-3149-7

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