【摘要】 [目的/意义]对国内文本情感分析的研究成果进行梳理与计量分析,有助于从不同角度了解主题研究状况、发文情况,对后续的研究具有一定的参考价值。[方法/过程]本文对发文期刊、作者团队进行统计分析,并利用共词分析法,研究关键词之间的联系,探讨近十年来在文本情感分析的研究热点及现状。[结果/结论]结果表明,我国近两年对文本情感分析的研究主要有基于情感词典的机器学习和神经网络的深度学习两种方法,文章最后指出了两种方法的研究现状及未来研究方向。更多还原

【Abstract】 [Purpose/Importance]The research results of text sentient analysis were sorted out and quantitatively analyzed,which was helpful to understand the status of subject research and publishing,and it had certain reference value for subsequent research.[methods/Procedures]This paper made a statistical analysis of the published journals and author teams,and uses co-word method to study the relationship between keywords,and discussed the research hot spots and current situation of text sentient analysis in the past decade.[Results/Conclusion]The results showed that the research on text sentiment analysis in China in the past two years mainly included two methods:machine learning based on emotion dictionary and deep learning based on neural network.At last,the paper pointed out the future research direction of the two methods.更多还原