Emotion Classification in Microblog Texts Using Class Sequential Rules

• DOI: 10.1609/aaai.v28i1.8709
• Publication Date: 2022-06-23T10:49:11Z
• Authors: Shiyang Wen; Xiaojun Wan
• Keywords: Microblogging; Sadness; Sentiment Analysis; Surprise

This paper studies the problem of emotion classification in microblog texts. Given a text which consists several sentences, we classify its as anger, disgust, fear, happiness, like, sadness or surprise if available. Existing methods can be categorized lexicon based machine learning methods. However, due to some intrinsic characteristics texts, previous using these always get unsatisfactory results. introduces novel approach on class sequential rules for The first obtains two potential labels each sentence by an and respectively, regards data sequence. It then mines from dataset finally derives new features mined Experimental results Chinese benchmark show superior performance proposed approach.