Assessment of Off-the-Shelf SE-specific Sentiment Analysis Tools: An Extended Replication Study
arXiv:2010.10172 · doi:10.1007/s10664-021-09960-w
Abstract
Sentiment analysis methods have become popular for investigating human communication, including discussions related to software projects. Since general-purpose sentiment analysis tools do not fit well with the information exchanged by software developers, new tools, specific for software engineering (SE), have been developed. We investigate to what extent SE-specific tools for sentiment analysis mitigate the threats to conclusion validity of empirical studies in software engineering, highlighted by previous research. First, we replicate two studies addressing the role of sentiment in security discussions on GitHub and in question-writing on Stack Overflow. Then, we extend the previous studies by assessing to what extent the tools agree with each other and with the manual annotation on a gold standard of 600 documents. We find that different SE-specific sentiment analysis tools might lead to contradictory results at a fine-grain level, when used 'off-the-shelf'. Conversely, platform-specific tuning or retraining might be needed to take into account differences in platform conventions, jargon, or document lengths.
arXiv commentAccepted for publication in Empirical Software Engineering
References in corpus (10)
- SMOTE: Synthetic Minority Over-sampling Technique
- Sentiment Polarity Detection for Software Development
- How to Ask for Technical Help? Evidence-based Guidelines for Writing Questions on Stack Overflow
- Mining Valence, Arousal, and Dominance - Possibilities for Detecting Burnout and Productivity?
- A Benchmark Study on Sentiment Analysis for Software Engineering Research
- Can We Use SE-specific Sentiment Analysis Tools in a Cross-Platform Setting?
- SEntiMoji: An Emoji-Powered Learning Approach for Sentiment Analysis in Software Engineering
- Bootstrapping a Lexicon for Emotional Arousal in Software Engineering
- How angry are your customers? Sentiment analysis of support tickets that escalate
- Love, Joy, Anger, Sadness, Fear, and Surprise: SE Needs Special Kinds of AI: A Case Study on Text Mining and SE
Cited by in corpus (4)
- The "Shut the f**k up" Phenomenon: Characterizing Incivility in Open Source Code Review Discussions
- Revisiting Sentiment Analysis for Software Engineering in the Era of Large Language Models
- Development and Application of Sentiment Analysis Tools in Software Engineering: A Systematic Literature Review
- On the Limitations of Combining Sentiment Analysis Tools in a Cross-Platform Setting