{"title":"Sentiment analysis of movie reviews: A new feature-based heuristic for aspect-level sentiment classification","authors":"V. K. Singh, Rajesh Piryani, A. Uddin, P. Waila","doi":"10.1109/IMAC4S.2013.6526500","DOIUrl":null,"url":null,"abstract":"This paper presents our experimental work on a new kind of domain specific feature-based heuristic for aspect-level sentiment analysis of movie reviews. We have devised an aspect oriented scheme that analyses the textual reviews of a movie and assign it a sentiment label on each aspect. The scores on each aspect from multiple reviews are then aggregated and a net sentiment profile of the movie is generated on all parameters. We have used a SentiWordNet based scheme with two different linguistic feature selections comprising of adjectives, adverbs and verbs and n-gram feature extraction. We have also used our SentiWordNet scheme to compute the document-level sentiment for each movie reviewed and compared the results with results obtained using Alchemy API. The sentiment profile of a movie is also compared with the document-level sentiment result. The results obtained show that our scheme produces a more accurate and focused sentiment profile than the simple document-level sentiment analysis.","PeriodicalId":403064,"journal":{"name":"2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"209","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMAC4S.2013.6526500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 209
Abstract
This paper presents our experimental work on a new kind of domain specific feature-based heuristic for aspect-level sentiment analysis of movie reviews. We have devised an aspect oriented scheme that analyses the textual reviews of a movie and assign it a sentiment label on each aspect. The scores on each aspect from multiple reviews are then aggregated and a net sentiment profile of the movie is generated on all parameters. We have used a SentiWordNet based scheme with two different linguistic feature selections comprising of adjectives, adverbs and verbs and n-gram feature extraction. We have also used our SentiWordNet scheme to compute the document-level sentiment for each movie reviewed and compared the results with results obtained using Alchemy API. The sentiment profile of a movie is also compared with the document-level sentiment result. The results obtained show that our scheme produces a more accurate and focused sentiment profile than the simple document-level sentiment analysis.