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数据分析与知识发现  2020, Vol. 4 Issue (1): 1-11
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1华中师范大学信息管理学院 武汉430079
2威斯康星大学密尔沃基分校信息研究院 密尔沃基 53211
A Survey of Sentiment Analysis on Social Media
Ying Tan1(),Jin Zhang2,Lixin Xia1
1School of Information Management, Central China Normal University, Wuhan 430079, China
2School of Information Studies, University of Wisconsin-Milwaukee, Milwaukee 53211, United State
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【目的】 调研近年来社交媒体情境下的情感分析相关研究,重点介绍情感挖掘的任务和方法。【文献范围】 利用Web of Science核心数据库检索2015年-2019年间,主题为Social Media和Sentiment Analysis的文献,并结合引文分析和浏览的方法补充文献集,共计收集163篇并引用代表性文献91篇。【方法】 针对社交媒体情境下的情感分析研究方向、技术和应用进行内容分析。【结果】 归纳10余种情感分析任务,总结适用于社交媒体平台的情感分析改进方法,并论述了这些情感分析结果的应用领域。【局限】 未深入解析情感分析算法的步骤和过程。【结论】 本文分析了情感分析研究的现有核心技术和改进方向,发现了该领域在社交媒体情境下的不同任务和挑战。

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关键词 社交媒体情感分析情感分析任务    

[Objective] This paper investigates recent researches addressing sentiment analysis on social media.[Coverage] 163 papers in total are collected and 91 articles are cited for this review, covering articles subject on social media and sentiment analysis retrieved from Web of Science Core Collection during 2015-2019, and a supplement from citation analysis and browsing.[Methods] Content analysis is used for exploring task, technology, and application of sentiment analysis on social media.[Results] A variety of sentiment analysis tasks are summarized, refine sentiment analysis techniques on social media platforms are clarified, application fields are discussed as well.[Limitations] There is no in-depth analysis of the step and procedure for the sentiment analysis algorithm.[Conclusions] The findings provide an overview of sentiment analysis study, including the state-of-the-art technique, application and challenges on social media platforms.

Key wordsSocial Media    Sentiment Analysis    Sentiment Analysis Task
收稿日期: 2019-06-27      出版日期: 2020-03-14
ZTFLH:  TP391.1  
通讯作者: 谭荧     E-mail:
谭荧,张进,夏立新. 社交媒体情境下的情感分析研究综述[J]. 数据分析与知识发现, 2020, 4(1): 1-11.
Ying Tan,Jin Zhang,Lixin Xia. A Survey of Sentiment Analysis on Social Media. Data Analysis and Knowledge Discovery, 2020, 4(1): 1-11.
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Fig.1  情感分类技术
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