![]() 2010), learning how to complete procedural tasks (Lee and Lehto 2013), and even browsing content shared by others just for fun and killing time (Ellison et al. 2015), searching for specific information and knowledge (Zahn et al. Today’s SNS platforms provide many functions, including presenting personal opinions and feelings on things (Tang and Hew 2017), sharing photographs and videos (Gibbs et al. 2006 Hargittai 2007 Fogel and Nehmad 2009), a substantial proportion of the population in many countries, who rely heavily on SNS platforms for social engagement, spend a significant amount of time on those platforms. According to previous research (Ellison et al. Platforms such as Facebook, Tencent’s QQ, and WeChat belong to social networking services (SNS), enabling their users to construct and maintain social relations in cyberspace (Jung and Lee 2011). For instance, in the USA, the big four-Google, Amazon, Facebook, and Apple-are known as GAFA (Miguel and Casado 2016), and in China, the big three-Baidu, Alibaba, and Tencent-are known as BAT (Keane 2016). An interesting and widespread phenomenon is the existence of large firms, whose platforms have significantly more users than their competitors, nearly monopolizing regional or national markets in each Internet service domain. The late entrant platform, comprising a major innovation, tends to fail when competing with the incumbent monopoly due to “network externalities.” Even when two competing platforms continue to propose innovations, and they will alternately lead the competition due to those innovations, this type of replacement of their competitive positions in the market may only occur a few times and then disappear completely. Based on this model, it was found that, in any case, one online interpersonal communication platform will eventually monopolize the market, either partly or entirely. Taken together, this bottom-up simulation model could reproduce and anticipate the applied competition process associated with such platforms. In this regard, the simulation results were compared to practical cases. ![]() ![]() Three scenarios were designed for this study to simulate typical modes of competition. The evolution of online interpersonal communication networks, and innovations proposed by online interpersonal communication platforms, would also impact this process by affecting individual selection on those platforms. ![]() Individual platform selection serves as the micro-foundation for the study. This paper aims to simulate and analyze this process from a bottom-up perspective. The competition of interpersonal communication platforms is a complex process affected by various factors. ![]()
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