摘要为了解国内外情感分析领域的研究状况，揭示该领域的知识结构、研究热点与发展动态，本文采用共被引分析、聚类分析、共词分析、战略坐标分析等方法，借助CiteSpace、UCINET、BICOMB、SPSS等软件，对Web of Science数据库收录的以情感分析为主题的相关文献进行计量分析与知识图谱绘制。分析结果表明，情感分析的应用、深度学习与神经网络、电子商务下的产品评论、事物情感特征评分、社交网络下用户生成内容、语义定向广告技术以及文本语言属性分析构建了情感分析的知识结构，产品评论与口碑、数据挖掘与人工智能、无监督学习、Hadoop-MapReduce与支持向量机以及神经网络与深度学习为该领域的研究热点，而顾客评论、推荐系统、极性分类、主题模型、电影评论、推特数据将是未来该领域主要研究方向。
周建, 刘炎宝, 刘佳佳. 情感分析研究的知识结构及热点前沿探析[J]. 情报学报, 2020, 39(1): 111-124.
Zhou Jian, Liu Yanbao, Liu Jiajia. Exploration of Intellectual Structure and Hot Issues in Sentiment Analysis Research. 情报学报, 2020, 39(1): 111-124.
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