Md. Akhter-Uz-Zaman Ashik, S. Shovon, Summit Haque
{"title":"Data Set For Sentiment Analysis On Bengali News Comments And Its Baseline Evaluation","authors":"Md. Akhter-Uz-Zaman Ashik, S. Shovon, Summit Haque","doi":"10.1109/ICBSLP47725.2019.201497","DOIUrl":null,"url":null,"abstract":"The biggest challenge of Bengali language processing is creating a strong data set to do research on. The main focus of this paper is to introduce an authentic and credible data set and this dataset is open for all to be used for educational purposes1 for Bengali sentiment analysis where the data was extracted from a well known online news portal’s user comments. Here comments on various news were scraped, and for detecting the true sentiments of the sentences, five labels of sentiments were used. An online crowd sourcing platform was used for data annotation. To ensure the credibility and validity of the data set, every entry of the data set was tagged three times. Three models of text classification were used for baseline evaluation to check the validity of the data set. This data set might be of valuable help for future works and researches on Bengali sentiment analysis.","PeriodicalId":413077,"journal":{"name":"2019 International Conference on Bangla Speech and Language Processing (ICBSLP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Bangla Speech and Language Processing (ICBSLP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBSLP47725.2019.201497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
The biggest challenge of Bengali language processing is creating a strong data set to do research on. The main focus of this paper is to introduce an authentic and credible data set and this dataset is open for all to be used for educational purposes1 for Bengali sentiment analysis where the data was extracted from a well known online news portal’s user comments. Here comments on various news were scraped, and for detecting the true sentiments of the sentences, five labels of sentiments were used. An online crowd sourcing platform was used for data annotation. To ensure the credibility and validity of the data set, every entry of the data set was tagged three times. Three models of text classification were used for baseline evaluation to check the validity of the data set. This data set might be of valuable help for future works and researches on Bengali sentiment analysis.