Chenyang Zhao, Peng Zhang, Jing Liu, Juan Wang, Jiyang Zhang
{"title":"Research on Domain Emotion Dictionary Construction Method based on Improved SO-PMI Algorithm","authors":"Chenyang Zhao, Peng Zhang, Jing Liu, Juan Wang, Jiyang Zhang","doi":"10.1145/3508230.3508233","DOIUrl":null,"url":null,"abstract":"The analysis of netizens' emotional tendency after emergencies is an important means for the government to understand netizens' mentality and guide public opinion. Constructing a scientific and reasonable domain emotion dictionary is an important part of accurate emotion analysis of Internet users. Currently, there are few sentiment dictionaries in the field of college education. This article proposes an improved SO-PMI method for constructing emotional dictionaries in the field of college education. Use TF-IDF to sort the importance of emotional seed words, modify the field importance of the SO-PMI extended word set, and a basic emotional dictionary formed by combining Dalian Polytechnic and HowNet emotional dictionary, and finally formed an emotional dictionary in the field of college education. According to the judgment of interrogative sentences and exclamation sentences, the calculation rules of sentiment intensity of sentences are revised. The experimental results show that this method has achieved good results on the actual Weibo comment data set.","PeriodicalId":252146,"journal":{"name":"Proceedings of the 2021 5th International Conference on Natural Language Processing and Information Retrieval","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 5th International Conference on Natural Language Processing and Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3508230.3508233","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The analysis of netizens' emotional tendency after emergencies is an important means for the government to understand netizens' mentality and guide public opinion. Constructing a scientific and reasonable domain emotion dictionary is an important part of accurate emotion analysis of Internet users. Currently, there are few sentiment dictionaries in the field of college education. This article proposes an improved SO-PMI method for constructing emotional dictionaries in the field of college education. Use TF-IDF to sort the importance of emotional seed words, modify the field importance of the SO-PMI extended word set, and a basic emotional dictionary formed by combining Dalian Polytechnic and HowNet emotional dictionary, and finally formed an emotional dictionary in the field of college education. According to the judgment of interrogative sentences and exclamation sentences, the calculation rules of sentiment intensity of sentences are revised. The experimental results show that this method has achieved good results on the actual Weibo comment data set.