{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/sentiment-polarity-detection-for-software","title":"Sentiment Polarity Detection for Software Development","arxiv_id":"1709.02984","date":"2017-09-09","proceeding":null,"authors":["Fabio Calefato","Filippo Lanubile","Federico Maiorano","Nicole Novielli"],"abstract":"The role of sentiment analysis is increasingly emerging to study software\ndevelopers' emotions by mining crowd-generated content within social software\nengineering tools. However, off-the-shelf sentiment analysis tools have been\ntrained on non-technical domains and general-purpose social media, thus\nresulting in misclassifications of technical jargon and problem reports. Here,\nwe present Senti4SD, a classifier specifically trained to support sentiment\nanalysis in developers' communication channels. Senti4SD is trained and\nvalidated using a gold standard of Stack Overflow questions, answers, and\ncomments manually annotated for sentiment polarity. It exploits a suite of both\nlexicon- and keyword-based features, as well as semantic features based on word\nembedding. With respect to a mainstream off-the-shelf tool, which we use as a\nbaseline, Senti4SD reduces the misclassifications of neutral and positive posts\nas emotionally negative. To encourage replications, we release a lab package\nincluding the classifier, the word embedding space, and the gold standard with\nannotation guidelines.","url_abs":"http://arxiv.org/abs/1709.02984v2","url_pdf":"http://arxiv.org/pdf/1709.02984v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"sentiment-polarity-detection-for-software","repo_url":"https://github.com/collab-uniba/Senti4SD","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}