Fabio Calefato, F. Lanubile, Nicole Novielli, L. Quaranta
{"title":"EMTk - The Emotion Mining Toolkit","authors":"Fabio Calefato, F. Lanubile, Nicole Novielli, L. Quaranta","doi":"10.1109/SEmotion.2019.00014","DOIUrl":null,"url":null,"abstract":"The Emotion Mining Toolkit (EMTk) is a suite of modules and datasets offering a comprehensive solution for mining sentiment and emotions from technical text contributed by developers on communication channels. The toolkit is written in Java, Python, and R, and is released under the MIT open source license. In this paper, we describe its architecture and the benchmark against the previous, standalone versions of our sentiment analysis tools. Results show large improvements in terms of speed.","PeriodicalId":181587,"journal":{"name":"2019 IEEE/ACM 4th International Workshop on Emotion Awareness in Software Engineering (SEmotion)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 4th International Workshop on Emotion Awareness in Software Engineering (SEmotion)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEmotion.2019.00014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
The Emotion Mining Toolkit (EMTk) is a suite of modules and datasets offering a comprehensive solution for mining sentiment and emotions from technical text contributed by developers on communication channels. The toolkit is written in Java, Python, and R, and is released under the MIT open source license. In this paper, we describe its architecture and the benchmark against the previous, standalone versions of our sentiment analysis tools. Results show large improvements in terms of speed.