B. Lin, Fiorella Zampetti, R. Oliveto, M. D. Penta, Michele Lanza, G. Bavota
{"title":"软件工程情感分析的两个数据集","authors":"B. Lin, Fiorella Zampetti, R. Oliveto, M. D. Penta, Michele Lanza, G. Bavota","doi":"10.1109/ICSME.2018.00084","DOIUrl":null,"url":null,"abstract":"Software engineering researchers have used sentiment analysis for various purposes, such as analyzing app reviews and detecting developers' emotions. However, most existing sentiment analysis tools do not achieve satisfactory performance when used in software-related contexts, and there are not many ready-to-use datasets in this domain. To facilitate the emergence of better tools and sufficient validation of sentiment analysis techniques, we present two datasets with labeled sentiments, which are extracted from mobile app reviews and Stack Overflow discussions, respectively. The web app we created to support the labeling of the Stack Overflow dataset is also provided.","PeriodicalId":6572,"journal":{"name":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","volume":"1 1","pages":"712-712"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Two Datasets for Sentiment Analysis in Software Engineering\",\"authors\":\"B. Lin, Fiorella Zampetti, R. Oliveto, M. D. Penta, Michele Lanza, G. Bavota\",\"doi\":\"10.1109/ICSME.2018.00084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software engineering researchers have used sentiment analysis for various purposes, such as analyzing app reviews and detecting developers' emotions. However, most existing sentiment analysis tools do not achieve satisfactory performance when used in software-related contexts, and there are not many ready-to-use datasets in this domain. To facilitate the emergence of better tools and sufficient validation of sentiment analysis techniques, we present two datasets with labeled sentiments, which are extracted from mobile app reviews and Stack Overflow discussions, respectively. The web app we created to support the labeling of the Stack Overflow dataset is also provided.\",\"PeriodicalId\":6572,\"journal\":{\"name\":\"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)\",\"volume\":\"1 1\",\"pages\":\"712-712\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSME.2018.00084\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSME.2018.00084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Two Datasets for Sentiment Analysis in Software Engineering
Software engineering researchers have used sentiment analysis for various purposes, such as analyzing app reviews and detecting developers' emotions. However, most existing sentiment analysis tools do not achieve satisfactory performance when used in software-related contexts, and there are not many ready-to-use datasets in this domain. To facilitate the emergence of better tools and sufficient validation of sentiment analysis techniques, we present two datasets with labeled sentiments, which are extracted from mobile app reviews and Stack Overflow discussions, respectively. The web app we created to support the labeling of the Stack Overflow dataset is also provided.