Analysis of an emotional contagion detection algorithm based on sentiment evaluation

dc.contributor.advisorBenedicenti, Luigi
dc.contributor.authorArora, Arleen Kaur
dc.date.accessioned2024-03-05T14:22:45Z
dc.date.available2024-03-05T14:22:45Z
dc.date.issued2023-12
dc.description.abstractEmotional contagion, or the transfer of emotions between individuals, is a well-studied phenomenon in social psychology. In recent years, researchers have become interested in understanding how emotional contagion can impact team dynamics in software development, particularly on GitHub where communication takes place primarily online. In this study, we propose an approach to detect emotional contagion in collaborative software development platform using sentiment analysis tool available in Mathematica. This approach is based on a previously published framework. We collected data from several GitHub repositories and analyzed the emotional content of developers’ comments to identify patterns of emotional contagion. Our findings suggest that emotional contagion exists and the algorithm defined can be used on various data sets. Our method is applied on five GitHub repositories, however the method is general and can be reused for experimental validation.
dc.description.copyright© Arleen Kaur Arora, 2023
dc.format.extentvii, 92
dc.format.mediumelectronic
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/37743
dc.language.isoen
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineComputer Science
dc.titleAnalysis of an emotional contagion detection algorithm based on sentiment evaluation
dc.typemaster thesis
oaire.license.conditionother
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.C.S.

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