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Collective actions from online to offline: External public pressure or internal structural factors

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  • Lu, Peng
  • Zhang, Yuan
  • Xiang, Yuan

Abstract

Besides of traditional (offline) collective actions, more and more people in the big data era are prone to launch online collective actions via Twitter & Facebook in USA and Weibo & Wechat in China. Although related factors such as organizational prompts, social prompts, and self-initiation are investigated to explore why the online collective actions prevails, the key scientific question why and how online collective actions transfer into offline collective actions remains unclear. Based on existing researches, the dual-pathway model is proposed to investigate the macro-level transfer mechanism of the online collective actions. The dual-pathway mechanism contains two chains, the external chain and internal chains. The external chain believes that the External pressure from public focus (online browse, public discussion, and individual interaction) leads online collective actions into offline collective action; the internal chain believes that the Internal structural factors (Interest, Rule, and Moral) have strong and positive effects on the online–offline transition of collective actions. It is proposed by the dual-pathway model that both the external and internal chains may have influences on the online–offline transfer of collective actions. Based on the big data of related online collective actions, the related variables of the dual-pathway model are operationalized to check or compare the two chains. It suggests that the External has weak effects and the Internal chain has strong effects. Besides, the summation of structural effects (interest + rule + moral), which is deemed as the kernel, shows the stronger effects on the transition.

Suggested Citation

  • Lu, Peng & Zhang, Yuan & Xiang, Yuan, 2019. "Collective actions from online to offline: External public pressure or internal structural factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    • Handle: RePEc:eee:phsmap:v:533:y:2019:i:c:s0378437119304947
    DOI: 10.1016/j.physa.2019.04.125
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    Cited by:

    1. Zhang, Yaozeng & Ma, Jing & Fang, Fanshu, 2024. "How social bots can influence public opinion more effectively: Right connection strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).

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