Understanding Usefulness in Developer Explanations on Stack Overflow
Martin Obaidi, Kushtrim Qengaj, Hannah Deters, Jakob Droste, Marc Herrmann, Kurt Schneider, Jil Kl\"under

TL;DR
This study analyzes Stack Overflow explanations to identify features that influence their perceived usefulness, revealing that structural and contextual factors like length and timing have moderate effects, while sentiment has little impact.
Contribution
It provides an empirical analysis of explanation features affecting usefulness in developer communication, with open data and insights for improving technical explanations.
Findings
Explanation length positively correlates with usefulness.
Code inclusion and author reputation have moderate effects.
Sentiment polarity has negligible influence.
Abstract
Explanations are essential in software engineering (SE) and requirements communication, helping stakeholders clarify ambiguities, justify design choices, and build shared understanding. Online Q&A forums such as Stack Overflow provide large-scale settings where such explanations are produced and evaluated, offering valuable insights into what makes them effective. While prior work has explored answer acceptance and voting behavior, little is known about which specific features make explanations genuinely useful. The relative influence of structural, contextual, and linguistic factors, such as content richness, timing, and sentiment, remains unclear. We analyzed 3,323 questions and 59,398 answers from Stack Overflow, combining text analysis and statistical modeling to examine how explanation attributes relate to perceived usefulness (normalized upvotes). Structural and contextual…
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Taxonomy
TopicsSoftware Engineering Research · Software Engineering Techniques and Practices · Open Source Software Innovations
