Uncovering the roots of player dissatisfaction in MOBA mobile games: a text mining and complex network theory approach to negative online reviews
by Yujie Zhan; Zunxiang Qiu; Xinchun Li; Jianping Shang; Quanlong Liu; Zishuo Zhao
International Journal of Sensor Networks (IJSNET), Vol. 42, No. 3, 2023

Abstract: Exploring the influencing factors of player experience perception in multiplayer online battle arena (MOBA) mobile games is essential to improve game competitiveness and player stickiness. Existing studies on this topic have primarily focused on positive aspects of player experience, relying on questionnaire data, which suffers from limitations like small data sample size, high survey cost, and subjective conclusions. Moreover, factors influencing player dissatisfaction, which is crucial for understanding player attrition, remain understudied. To address these gaps, this paper analyses 42,511 negative online reviews of MOBA games using text mining technology and complex network theory. The chi-square statistics algorithm identifies five experience dimensions and their corresponding 25 game attributes related to player dissatisfaction. We identify eight key factors affecting player dissatisfaction by constructing a player dissatisfaction perception network and analysing network centrality. The main path analysis then identifies two critical formation chains of players' negative emotions. Our approach yields more accurate and objective insights, which can help merchants optimise their gaming products and increase customer retention.

Online publication date: Thu, 27-Jul-2023

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