Topic mining of real-time discussions: what catches the attention of live-streaming esports viewers?

联盟 多项式logistic回归 计算机科学 鉴定(生物学) 潜在Dirichlet分配 广告 民族志 主题模型 社会学 业务 人工智能 机器学习 物理 天文 生物 植物 人类学
作者
Wenche Wang,Jiajia Fan
出处
期刊:European Sport Management Quarterly [Taylor & Francis]
卷期号:24 (2): 323-344 被引量:16
标识
DOI:10.1080/16184742.2022.2117397
摘要

Research question To better understand esports consumer demand, this study derived topics from real-time viewer comments during live streams of two professional esports leagues, King Pro League (KPL) and CrossFire Pro League (CFPL). We investigated structural factors that drew viewers’ attention to each topic.Research methods Using data from Douyu.com, we collected 1,111,177 real-time comments on 126 KPL matches and 233,869 comments on 96 CFPL matches. We employed a digital ethnography approach to discern the fan identification of viewers who contributed to comments. We applied guided Latent Dirichlet Allocation (LDA) to extract topics in these comments. We examined structural factors that affect viewers’ interest in each topic using a multinomial logit regression.Results and findings Only a small proportion of viewers who commented during live-streaming esports games were identified as fans of competing teams. Viewers paid most attention to the excitement of the game. Commentators and in-streaming activities also captured viewers’ attention. Esports fans tended to focus on players and teams whereas general observers were more attuned to game-related skills and knowledge.Implications We take the attention economy as a theoretical framework to understand esports consumers’ interests and demonstrate the structure of consumer demand for various aspects of esports. We provide insight to help esports organizations and live-streaming platforms effectively attract viewers.
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