基于主题模型的广播媒体社交媒体内容分析

Sangun Park
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引用次数: 3

摘要

提交:2016年1月30日,1 st修订:5月25日,2016年接受:2016年5月27日*이논문학은2014년도경기대학교연구년수혜로연구되었음。许多人在个人博客和推特等社交媒体上与其他观众分享他们的电视体验。这意味着广播媒体,尤其是电视,会影响社交媒体上的反应。此外,这些回应还会反过来影响广播媒体的收视率。社交电视试图通过分析电视相关的社会行为,将这种关系运用到广告等营销活动中。然而,他们中的大多数人只使用了社交媒体回应的数量。本研究通过话题建模分析特定电视剧在社交媒体上的回应主体,以及特定时间段内热门话题的变化与该剧收视率的关系。选取了2014年的5部代表性韩剧,并在韩国代表性门户网站naver.com上收集了韩剧的收视率等博客内容。本文提出的分析框架包括博客抓取、主题建模和主题趋势分析三个步骤。我们从主题趋势分析的结果中发现了一些启示。首先,社交媒体上有关于电视剧的具体话题。其次,话题与收视率之间存在一些有意义的关系。最后,收视率高的电视剧和收视率低的电视剧的话题之间存在差异。关键词:社交媒体,广播媒体,话题建模,话题趋势
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Social Media Contents about Broadcast Media through Topic Modeling
Submitted:January 30, 2016 1 st Revision:May 25, 2016 Accepted:May 27, 2016 * 이 논문은 2014학년도 경기대학교 연구년 수혜로 연구되었음. ** 경기대학교 경상대학 경영정보학과 부교수 Numerous people share their TV experience with other viewers on social media such as personal blogs and Twitter. It means that broadcast media, especially TV, affects the responses on social media. Moreover, the responses affect broadcast media ratings back. Social TV tried to use the relationship in marketing activities such as advertisement by analyzing the TV related social behavior. However, most of them used just the quantities of social media responses. This study analyzes the subjects of the responses on social media about specific TV dramas through topic modeling, and the relationship between the changes of popular topics and viewer ratings of the drama over specified periods. Five representative Korean dramas of 2014 were selected and Blog contents including viewer ratings about the dramas were collected from naver.com which is the representative portal in South Korea. The proposed analysis framework consists of three steps which are Blogs crawling, topic modeling, and topic trend analysis. We found some implications from the results of the topic trend analysis. Firstly, there were specific topics on dramas in social media. Secondly, the topics had some meaningful relationships with viewer ratings. Lastly, there were differences between the topics of dramas with higher viewer ratings and those with lower viewer ratings. Keyword:Social Media, Broadcast Media, Topic Modeling, Topic Trends 韓國IT서비스學會誌 第15卷 第2號 2016年 6月, pp.81-92
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