体育社交媒体研究中的机器学习:实际应用和机会

IF 2 Q2 COMMUNICATION
James Du, Yoseph Z. Mamo, C. Floyd, Niveditha Karthikeyan, J. James
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引用次数: 1

摘要

随着社交媒体研究在体育传播和营销领域的迅速普及,我们看到其认识论的复杂性也随之上升。尽管有这种增长,但该领域对方法论问题和影响的关注较少。鉴于机器学习的发展,当前研究的首要目标是回应对创新方法方法的呼吁,以推进社交媒体研究领域的知识。具体来说,我们(a)从方法论的角度评估体育社交媒体研究的现状,特别关注机器学习;(b)提出实证说明,说明体育学者如何从自然语言处理和衍生主题建模技术的进步中受益;(c)讨论机器学习如何提高社交媒体研究的严谨性和促进理论发展;(d)为未来利用机器学习的体育社交媒体研究提供潜在的机会和方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning in Sport Social Media Research: Practical Uses and Opportunities
In tandem with the burgeoning popularity of social media research in the field of sport communication and marketing, we are witnessing a concomitant rise in its epistemological sophistication. Despite this growth, the field has given less attention to methodological issues and implications. In light of the development of machine learning, the overarching goal of the current research was to answer the call for innovative methodological approaches to advance knowledge in the area of social media research. Specifically, we (a) assess the current state of sport social media research from a methodological perspective, with a particular focus on machine learning; (b) present an empirical illustration to demonstrate how sport scholars can benefit from the advancement in natural language processing and the derivative topic modeling techniques; (c) discuss how machine learning could enhance the rigor of social media research and improve theory development; and (d) offer potential opportunities and directions for the future sport social media research that utilizes machine learning.
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来源期刊
CiteScore
3.70
自引率
5.60%
发文量
36
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