3.8 Proceedings Paper

Bootstrapping a Lexicon for Emotional Arousal in Software Engineering

出版社

IEEE
DOI: 10.1109/MSR.2017.47

关键词

Sentiment Analysis; Lexicon; Emotional Arousal; Issue Report; Empirical Software Engineering

资金

  1. Academy of Finland [298020]
  2. project EmoQuest
  3. MIUR under SIR program
  4. Academy of Finland (AKA) [298020, 298020] Funding Source: Academy of Finland (AKA)

向作者/读者索取更多资源

Emotional arousal increases activation and performance but may also lead to burnout in software development. We present the first version of a Software Engineering Arousal lexicon (SEA) that is specifically designed to address the problem of emotional arousal in the software developer ecosystem. SEA is built using a bootstrapping approach that combines word embedding model trained on issue-tracking data and manual scoring of items in the lexicon. We show that our lexicon is able to differentiate between issue priorities, which are a source of emotional activation and then act as a proxy for arousal. The best performance is obtained by combining SEA (428 words) with a previously created general purpose lexicon by Warriner et al. (13,915 words) and it achieves Cohen's d effect sizes up to 0.5.

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