Information Acquisition, Persuasion, and Group Conformity of Online Tribalism: Does User Activeness Matter?

Information Acquisition, Persuasion, and Group Conformity of Online Tribalism: Does User Activeness Matter?

Jie Meng (Loughborough University, UK)
Copyright: © 2022 |Pages: 23
DOI: 10.4018/IJEBR.288036
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Abstract

Though empirically some research suggests the linkage of better communication effect with active users' presence, no existing clues are found on the user activeness at the micro level to contribute to the virtual community's aggregate-level health and vitality. This paper models the interpersonal communication process via a multi-agent, self-reasoning model. It considers each agent’s information value and conformity value, two key constructs adopted in this paper. This paper adopts simulated experiments to identify active users based on individuals’ behavioural characteristics, screen out typical users of different activeness levels, and reveal causalities among the outcomes. The findings show that users' activeness determines the information vitality and influence of information dissemination and substantially impacts the dynamics of user-groups. The author concludes with a discussion of the theoretical and methodological contributions and pinpoints these findings for marketers to improve online customer relationship management.
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Introduction

The fast-growing virtual platform has witnessed lots of myths in business. Virtual community incubates extensive customer communications where consumers demonstrate some tribal behaviors in an informal network based on a common interest and affiliation to a topic, a belief, a figure, a ritual, or a culture (Helmuth, Gouhier, Scyphers, & Mocarski, 2016; Kacprzak–Choiska, 2011). Typical examples include major question-and-answer platforms such as Quora with 300 million monthly unique visitors (Smith, 2019a) and Zhihu featured by 600 million monthly unique visitors (Smith, 2019b). However, research suggests that 1% of active users have contributed up to 70% of the total posts and deeply engaged with various online actions (G. Wang, Gill, Mohanlal, Zheng, & Zhao, 2013). A very similar statistic is also inferable from Zhihu Statistics (Smith, 2019b). Tribal behaviors enable forum users to influence each other by initiating, spreading, appraising, receiving, and internalizing beliefs via a social network. Undoubtedly, behind the nodes of the group network, some drives and consequences are interwoven, such as information exchange, self-esteem development, group attitude shaping, and social status development (Feliciani, Flache, & Tolsma, 2017; Sierra, Badrinarayanan, & Taute, 2016; D. Wang, Li, & Xiao, 2019).

Literature more or less casts partial lights on the presence of active users in various online activities (Araujo, Neijens, & Vliegenthart, 2017; De Veirman, Cauberghe, & Hudders, 2017), yet little systematic investigation has even been into the vision as “what features do those critical influencers own” and “how to identify them.” Some research has spotted that consumers attached different credence to information sources in terms of expertise, identity, or reputation (Harrigan et al., 2021), motivation (Mandel, Rucker, Levav, & Galinsky, 2017), testimony (Packard & Berger, 2017; Vithayathil, Dadgar, & Osiri, 2020). Influencers who attain a geometric growth in the number of followers and evolve as opinion-leaders due to their expertise or devotion to a conversation have a more significant influence on other users’ product adoption (Asamoah & Sharda, 2021; Casaló, Flavián, & Ibáñez-Sánchez, 2018). Notably, from vast literature, the incredible power of influencers is evident but attributed only to external intervention such as advertising, sponsored opinion leaders. At the same time, opposite to these emerging opinion leaders (e.g., “cewebrity”), the other type of influencer is cosponsored influencers (e.g., celebrity) who receive a reward to promote their brands by their extraordinary persuasiveness on millennials. Rare theories and empirical studies explain how peer-to-peer impacts grow as an endogenous outcome from virtual information exchange.

Despite various explanations of the influence of an online advisor, literature is scant about the emergence of “organic” influencers and understand their “activeness” with impacts on others and how influencers impact other members’ attitudinal shaping and decisions. These questions necessitate a comprehensive study to address research gaps as to how influencers and influence interact and evolve in action at an aggregate level. In view of so, this research has three research objectives.

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