A review on sentiment analysis and emotion detection from text

被引:307
作者
Nandwani, Pansy [1 ]
Verma, Rupali [1 ]
机构
[1] Punjab Engn Coll, Comp Sci & Engn Dept, Chandigarh, India
关键词
Affective computing; Natural language processing; Opinion mining; Pre-processing; Word embedding; HYBRID APPROACH; CLASSIFICATION; LEXICON; RECOGNITION; EXTRACTION; MODEL;
D O I
10.1007/s13278-021-00776-6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Social networking platforms have become an essential means for communicating feelings to the entire world due to rapid expansion in the Internet era. Several people use textual content, pictures, audio, and video to express their feelings or viewpoints. Text communication via Web-based networking media, on the other hand, is somewhat overwhelming. Every second, a massive amount of unstructured data is generated on the Internet due to social media platforms. The data must be processed as rapidly as generated to comprehend human psychology, and it can be accomplished using sentiment analysis, which recognizes polarity in texts. It assesses whether the author has a negative, positive, or neutral attitude toward an item, administration, individual, or location. In some applications, sentiment analysis is insufficient and hence requires emotion detection, which determines an individual's emotional/mental state precisely. This review paper provides understanding into levels of sentiment analysis, various emotion models, and the process of sentiment analysis and emotion detection from text. Finally, this paper discusses the challenges faced during sentiment and emotion analysis.
引用
收藏
页数:19
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