用马尔可夫链模型描述软件开发者的情感

IF 0.6 Q4 STATISTICS & PROBABILITY Electronic Journal of Applied Statistical Analysis Pub Date : 2020-02-05 DOI:10.1285/I20705948V13N1P96
Marco Ortu, C. Conversano, M. Marchesi, R. Tonelli, S. Counsell, Giuseppe Destefanis
{"title":"用马尔可夫链模型描述软件开发者的情感","authors":"Marco Ortu, C. Conversano, M. Marchesi, R. Tonelli, S. Counsell, Giuseppe Destefanis","doi":"10.1285/I20705948V13N1P96","DOIUrl":null,"url":null,"abstract":"In this paper, we present an analysis of more than 500K comments from open-sourcerepositories of software systems.Our aim is to empirically determine how developers interact with each otherunder certain psychological conditions generated by politeness, sentiment andemotion expressed within developers' comments.Developers involved in an open-source projects do not usually know each other; they mainly communicate through mailing lists, chat rooms, and tools such as issue tracking systems.The way in which they communicate affects the development process and the productivity of the people involved in the project.We evaluated politeness, sentiment and emotions of comments posted by developers and studied the communication flow to understand how they interacted in the presence of impolite and negative comments (and vice versa).Our analysis shows that when in presence of impolite or negative comments, the probability of the next comment being impolite or negative is 14% and 25%, respectively;  anger however,has a probability of 40% of being followed by a further anger comment.The result could help managers take control the development phases of a system, since social aspects can seriously affect a developer's productivity. In a distributed environment this may have a particular resonance.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"13 1","pages":"96-127"},"PeriodicalIF":0.6000,"publicationDate":"2020-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Describing Software Developers Affectiveness through Markov chain Models\",\"authors\":\"Marco Ortu, C. Conversano, M. Marchesi, R. Tonelli, S. Counsell, Giuseppe Destefanis\",\"doi\":\"10.1285/I20705948V13N1P96\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present an analysis of more than 500K comments from open-sourcerepositories of software systems.Our aim is to empirically determine how developers interact with each otherunder certain psychological conditions generated by politeness, sentiment andemotion expressed within developers' comments.Developers involved in an open-source projects do not usually know each other; they mainly communicate through mailing lists, chat rooms, and tools such as issue tracking systems.The way in which they communicate affects the development process and the productivity of the people involved in the project.We evaluated politeness, sentiment and emotions of comments posted by developers and studied the communication flow to understand how they interacted in the presence of impolite and negative comments (and vice versa).Our analysis shows that when in presence of impolite or negative comments, the probability of the next comment being impolite or negative is 14% and 25%, respectively;  anger however,has a probability of 40% of being followed by a further anger comment.The result could help managers take control the development phases of a system, since social aspects can seriously affect a developer's productivity. In a distributed environment this may have a particular resonance.\",\"PeriodicalId\":44770,\"journal\":{\"name\":\"Electronic Journal of Applied Statistical Analysis\",\"volume\":\"13 1\",\"pages\":\"96-127\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2020-02-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Journal of Applied Statistical Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1285/I20705948V13N1P96\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Journal of Applied Statistical Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1285/I20705948V13N1P96","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 1

摘要

在本文中,我们对来自软件系统开放源码存储库的50多万条评论进行了分析。我们的目标是通过经验来确定在某些心理条件下,开发者是如何与他人互动的,这些心理条件是由开发者评论中表达的礼貌、情绪和情绪所产生的。参与开源项目的开发人员通常彼此不认识;他们主要通过邮件列表、聊天室和诸如问题跟踪系统之类的工具进行交流。他们沟通的方式影响着开发过程和参与项目的人员的生产力。我们评估了开发者发表的评论的礼貌、情感和情绪,并研究了交流流程,以了解他们在出现不礼貌和负面评论时是如何互动的(反之亦然)。我们的分析表明,当出现不礼貌或负面评论时,下一条评论不礼貌或负面的概率分别为14%和25%;然而,愤怒有40%的可能性会引发更多的愤怒评论。结果可以帮助管理人员控制系统的开发阶段,因为社会方面会严重影响开发人员的生产力。在分布式环境中,这可能会产生特殊的共鸣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Describing Software Developers Affectiveness through Markov chain Models
In this paper, we present an analysis of more than 500K comments from open-sourcerepositories of software systems.Our aim is to empirically determine how developers interact with each otherunder certain psychological conditions generated by politeness, sentiment andemotion expressed within developers' comments.Developers involved in an open-source projects do not usually know each other; they mainly communicate through mailing lists, chat rooms, and tools such as issue tracking systems.The way in which they communicate affects the development process and the productivity of the people involved in the project.We evaluated politeness, sentiment and emotions of comments posted by developers and studied the communication flow to understand how they interacted in the presence of impolite and negative comments (and vice versa).Our analysis shows that when in presence of impolite or negative comments, the probability of the next comment being impolite or negative is 14% and 25%, respectively;  anger however,has a probability of 40% of being followed by a further anger comment.The result could help managers take control the development phases of a system, since social aspects can seriously affect a developer's productivity. In a distributed environment this may have a particular resonance.
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
CiteScore
1.40
自引率
14.30%
发文量
0
期刊最新文献
Exploratory Data Analysis of Accuracy of US Weather Forecastes Extended asymmetry model based on logit transformation and decomposition of symmetry for square contingency tables with ordered categories Generalized Quasi Lindley Distribution: Theoretical Properties, Estimation Methods, and Applications Almost unbiased ridge estimator in the count data regression models Does the elimination of work flexibility contribute to reducing wage inequality? Empirical evidence from Ecuador
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1