Bootstrapping a Lexicon for Emotional Arousal in Software Engineering

Abstract

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.