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Sentiment analysis for software engineering: how far can we go?

Lin, Bin ; Zampetti, Fiorella ; Bavota, Gabriele ; Di Penta, Massimiliano ; Lanza, Michele ; Oliveto, Rocco

2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE), 2018, p.94-104

New York, NY, USA: ACM

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  • Título:
    Sentiment analysis for software engineering: how far can we go?
  • Autor: Lin, Bin ; Zampetti, Fiorella ; Bavota, Gabriele ; Di Penta, Massimiliano ; Lanza, Michele ; Oliveto, Rocco
  • Assuntos: Information systems -- Information retrieval -- Retrieval tasks and goals -- Sentiment analysis ; Motion pictures ; NLP ; Sentiment analysis ; Software ; Software engineering ; Task analysis ; Training
  • É parte de: 2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE), 2018, p.94-104
  • Descrição: Sentiment analysis has been applied to various software engineering (SE) tasks, such as evaluating app reviews or analyzing developers' emotions in commit messages. Studies indicate that sentiment analysis tools provide unreliable results when used out-of-the-box, since they are not designed to process SE datasets. The silver bullet for a successful application of sentiment analysis tools to SE datasets might be their customization to the specific usage context. We describe our experience in building a software library recommender exploiting developers' opinions mined from Stack Overflow. To reach our goal, we retrained---on a set of 40k manually labeled sentences/words extracted from Stack Overflow---a state-of-the-art sentiment analysis tool exploiting deep learning. Despite such an effort- and time-consuming training process, the results were negative. We changed our focus and performed a thorough investigation of the accuracy of commonly used tools to identify the sentiment of SE related texts. Meanwhile, we also studied the impact of different datasets on tool performance. Our results should warn the research community about the strong limitations of current sentiment analysis tools.
  • Editor: New York, NY, USA: ACM
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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