{"title":"基于K均值聚类的微博数据情感分析","authors":"Agashini V. Kumar, K. Meera","doi":"10.1109/ICETET-SIP-2254415.2022.9791723","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to perform sentiment analysis on a microblogging data (Twitter data is taken for the experiment) using k means clustering algorithm. The main intention here is to study the conditions that may favor or not, sentiment analysis using k means clustering considering only two major sentiments as positive and negative. The other sentiments which are not of major interest are made into another cluster and the accuracy of the clusters thus formed is analyzed and meaningful conclusions from the same can be obtained.","PeriodicalId":117229,"journal":{"name":"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sentiment Analysis Using K Means Clustering on Microblogging Data Focused on Only the Important Sentiments\",\"authors\":\"Agashini V. Kumar, K. Meera\",\"doi\":\"10.1109/ICETET-SIP-2254415.2022.9791723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this paper is to perform sentiment analysis on a microblogging data (Twitter data is taken for the experiment) using k means clustering algorithm. The main intention here is to study the conditions that may favor or not, sentiment analysis using k means clustering considering only two major sentiments as positive and negative. The other sentiments which are not of major interest are made into another cluster and the accuracy of the clusters thus formed is analyzed and meaningful conclusions from the same can be obtained.\",\"PeriodicalId\":117229,\"journal\":{\"name\":\"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICETET-SIP-2254415.2022.9791723\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETET-SIP-2254415.2022.9791723","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sentiment Analysis Using K Means Clustering on Microblogging Data Focused on Only the Important Sentiments
The aim of this paper is to perform sentiment analysis on a microblogging data (Twitter data is taken for the experiment) using k means clustering algorithm. The main intention here is to study the conditions that may favor or not, sentiment analysis using k means clustering considering only two major sentiments as positive and negative. The other sentiments which are not of major interest are made into another cluster and the accuracy of the clusters thus formed is analyzed and meaningful conclusions from the same can be obtained.