基于社交大数据分析的体育动画成功研究——以扣篮综合症为例

Yong-Seok Jang
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引用次数: 0

摘要

本研究旨在通过社会大数据分析来分析体育动画的关键词、情感和感知。作为研究方法,利用社会矩阵大数据平台Textome进行文本挖掘、意见挖掘和语义网络分析。研究结果如下:首先,通过词频、TF-IDF和连接中心性分析,关键词First、slam dunk、movie、Japan、release、comic book、animation、sales、box office、audience都出现在了前10,确认了它们都是关键关键词。其次,通过意见挖掘分析,出现了积极词(76.38%)和消极词(23.61%),说明积极关键词较多。第三,通过CONCOR分析,形成了“体育动画内容”和“体育动画产品”两大类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study on the Success of Sports Animation using Social Big data analysis: Focusing on the Slam Dunk Syndrome
This study aims to analyze keywords, emotions, and perceptions of sports animation through social big data analysis. As a research method, text mining, opinion mining, and semantic network analysis were conducted using Textome, a social matrix big data platform. The research results are as follows. First, as a result of word frequency, TF-IDF, and connection centrality analysis, the keywords first, slam dunk, movie, Japan, release, comic book, animation, sales, box office, and audience all appeared in the top 10, confirming that they are key keywords. Second, as a result of opinion mining analysis, positive words (76.38%) appeared and negative words (23.61%), indicating that there are many positive keywords. Third, as a result of the CONCOR analysis, two groups were formed: ‘sports animation contents’ and ‘sports animation products’.
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