Analysis of players' experience perceptions of mobile games based on text mining and a complex network
by Yujie Zhan; Zunxiang Qiu; Jianping Shang; Xinchun Li; Quanlong Liu; Zishuo Zhao
International Journal of Sensor Networks (IJSNET), Vol. 42, No. 4, 2023

Abstract: Understanding the factors influencing mobile game experience perception is crucial for enhancing product competitiveness and fostering customer loyalty. Existing studies predominantly rely on questionnaires or interviews to gather data, which is potentially limited by the researcher's knowledge level. Moreover, there is a lack of heterogeneity in analysing positive and negative game experiences within current research. This study investigates 236,524 online mobile game reviews to address these shortcomings, employing text mining techniques and complex network theory. Utilising the combined term frequency-inverse document frequency (TF-IDF) and TextRank algorithms, we discern game attributes that players prioritise in their experience perception. Subsequently, we construct player experience perception networks to pinpoint key factors influencing satisfaction and dissatisfaction and the critical paths shaping positive and negative player emotions. Our findings reveal the perceptual dimensions of game experiences, their associated emotional traits, and the essential factors contributing to enjoyable and unfavourable experiences. This study advances mobile game experience research by unveiling the intricate formation mechanisms underlying players' perceptions of positive and negative experiences. Additionally, the proposed workflow introduces innovative perspectives for research methodologies in user product experience. Further details and implications of the results are thoroughly discussed in the main text.

Online publication date: Sun, 03-Sep-2023

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