软件工程文本情感分析的词典构建方法比较

M. R. Islam, M. Zibran
{"title":"软件工程文本情感分析的词典构建方法比较","authors":"M. R. Islam, M. Zibran","doi":"10.1109/ESEM.2017.67","DOIUrl":null,"url":null,"abstract":"Sentiment Analysis (SA) in Software Engineering (SE) texts suffers from low accuracies primarily due to the lack of an effective dictionary. The use of a domain-specific dictionary can improve the accuracy of SA in a particular domain. Building a domain dictionary is not a trivial task. The performance of lexical SA also varies based on the method applied to develop the dictionary. This paper includes a quantitative comparison of four dictionaries representing distinct dictionary building methods to identify which methods have higher/lower potential to perform well in constructing a domain dictionary for SA in SE texts.","PeriodicalId":213866,"journal":{"name":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","volume":"213 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"A Comparison of Dictionary Building Methods for Sentiment Analysis in Software Engineering Text\",\"authors\":\"M. R. Islam, M. Zibran\",\"doi\":\"10.1109/ESEM.2017.67\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sentiment Analysis (SA) in Software Engineering (SE) texts suffers from low accuracies primarily due to the lack of an effective dictionary. The use of a domain-specific dictionary can improve the accuracy of SA in a particular domain. Building a domain dictionary is not a trivial task. The performance of lexical SA also varies based on the method applied to develop the dictionary. This paper includes a quantitative comparison of four dictionaries representing distinct dictionary building methods to identify which methods have higher/lower potential to perform well in constructing a domain dictionary for SA in SE texts.\",\"PeriodicalId\":213866,\"journal\":{\"name\":\"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)\",\"volume\":\"213 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ESEM.2017.67\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESEM.2017.67","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19

摘要

软件工程(SE)文本中的情感分析(SA)由于缺乏有效的词典而导致准确率低。使用特定于领域的字典可以提高特定领域中SA的准确性。构建域字典不是一项简单的任务。词法情景分析的性能也因开发词典的方法而异。本文对代表不同词典构建方法的四种词典进行了定量比较,以确定哪些方法在构建SE文本中的SA领域词典方面具有更高/更低的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comparison of Dictionary Building Methods for Sentiment Analysis in Software Engineering Text
Sentiment Analysis (SA) in Software Engineering (SE) texts suffers from low accuracies primarily due to the lack of an effective dictionary. The use of a domain-specific dictionary can improve the accuracy of SA in a particular domain. Building a domain dictionary is not a trivial task. The performance of lexical SA also varies based on the method applied to develop the dictionary. This paper includes a quantitative comparison of four dictionaries representing distinct dictionary building methods to identify which methods have higher/lower potential to perform well in constructing a domain dictionary for SA in SE texts.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信