Welcome to Francis Academic Press

Academic Journal of Business & Management, 2023, 5(12); doi: 10.25236/AJBM.2023.051220.

Analysis of Population Competition and User Competition between Tiktok and WeChat

Author(s)

Yemin Huang1, Pengyang Xu2, Zhuang Xiong2

Corresponding Author:
Yemin Huang
Affiliation(s)

1School of Economics, Northeastern University at Qinhuangdao, Qinhuangdao, China

2School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, 066000, China

Abstract

Competition exists in many fields of nature and human society. In the current diverse new media competition in economic and life, precise and detailed user research is conducive to improving the competitiveness of enterprises. Whether Tiktok or wechat, their rise is inseparable from embracing the market demand. Competition for the number of users of the two is conducive to understanding the user needs, clarifying the development positioning, and defining the orientation of future product design. Therefore, it is necessary to study in depth the competition between Tiktok and wechat. Based on the empirical facts and the consideration of the appropriate simplified model, this paper first proposes four basic assumptions. Based on the two group competition models in the presence of competition, we transform the —— based on the special movement rules of market economy, introduce the concept of effective competition, and make it conform to the user competition between Tiktok and wechat. Then, according to the ratio relationship between user growth rate and competitive factor, the linkage law between Tiktok and the number of wechat users is discussed. Since both belong to the social application software of video communication, the core of which is manipulation and feedback, the user "psychological factor" is further introduced into the model to increase durability, playability and other indicators. Integrate the update of the application platform, discuss the situation and get the balance point. At the same time, we mined the user data of the platform, and discussed the user number competition between Tiktok and wechat based on the update situation of the platform and the user experience classification. It is found that the change curve of the number of users of Tiktok and wechat follows the s-shaped curve. In order to improve the user dependence, it is necessary to increase the maximum sample size of ——, that is, to improve the experience of user manipulation and feedback, rather than playing a zero-sum game between the two. The persistence and play of the APP are positively correlated with the change in the number of users, which is positively correlated with the increase and decrease of the user experience brought by the number of version updates, rather than simply depending on the number of updates. Only from the perspective of users, to improve the use experience of applications, and to clarify their own marketing strategy and strategic positioning, can they remain invincible in the competition of the number of users. The model established here is simple and feasible. They can be extended to competitive analysis of multiple groups and even a broad field of competitive analysis of various economic entities. According to the different conditions, the equilibrium level and the coexistence situation can be combined. After analytical verification, the model established in this paper has reasonable and practical significance.

Keywords

Two competition models between groups, Psychological analysis, User competition

Cite This Paper

Yemin Huang, Pengyang Xu, Zhuang Xiong. Analysis of Population Competition and User Competition between Tiktok and WeChat. Academic Journal of Business & Management (2023) Vol. 5, Issue 12: 116-121. https://doi.org/10.25236/AJBM.2023.051220.

References

[1] Li Dong, Xu Zhiming, Li Sheng, et al. Information diffusion in online social networks [J]. Journal of Computer Science, 2014, 37 (1): 189-206.

[2] Xu Xiaoke, Hu Haibo, Zhang Lun, et al. Computational communication studies on social networks [M]. Beijing: Higher Education Press, 2015.

[3] Extension and application of Yang Qian 2022 Lotka-Volterra model.

[4] Jin M, Zhang J, Huang T, et al. Research on Human Action Recognition Based on Global-Local Features of Video[C]// International Conference on Pattern Recognition and Machine Learning. IEEE, 2021.

[5] Shi Liping. Analysis of the effect of media cross-media competition based on the bilateral market [J]. Journal of Hunan University (Social Science Edition), 2013, 27 (1): 156-160.