DEVA

Abstract

Existing tools for automated sentiment analysis in software engineering text suffer from either or both of two limitations. First, they are developed for non-technical domain and perform poorly when operated on software engineering text. Second, those tools attempt to detect valence only, and cannot capture arousal or individual emotional states such as excitement, stress, depression, and relaxation.