转向堆栈溢出:遗留开发者论坛中的最佳答案预测

Fabio Calefato, F. Lanubile, Nicole Novielli
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引用次数: 29

摘要

背景:最近,越来越多的开发人员社区正在放弃他们的传统支持论坛,转向Stack Overflow。动机多种多样,但它们通常包括通过访问现代且非常成功的基础设施来实现更快的响应时间和更大的可见性。然而,迁移的一个缺点是,如果社区决定完全放弃遗留的开发人员论坛,那么以前站点上托管的历史和众包知识仍然是分开的,甚至会丢失。目标:增加现有的最佳答案预测研究的证据,这里我们表明,从技术角度来看,现有开发者论坛的内容可能会自动迁移到Stack Overflow,尽管大多数论坛不允许将问题标记为已解决,这是现代问答网站的一个显著特征。方法:我们用来自Stack Overflow的数据训练了一个二元分类器,然后用从Docusign(一个最近完成迁移的开发者论坛)上抓取的数据对其进行了测试。结果:我们的研究结果表明,只依赖于肤浅的语言(文本)特征,如答案长度和句子数量,结合其他特征,如答案的支持度和年龄,可以很容易地在接近实时的情况下预测出最佳答案,准确度很高。结论:研究结果为众包知识从传统论坛自动迁移到现代问答网站提供了初步但积极的证据。
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Moving to Stack Overflow: Best-Answer Prediction in Legacy Developer Forums
Context: Recently, more and more developer communities are abandoning their legacy support forums, moving onto Stack Overflow. The motivations are diverse, yet they typically include achieving faster response time and larger visibility through the access to a modern and very successful infrastructure. One downside of migration, however, is that the history and the crowdsourced knowledge hosted at previous sites remain separated or even get lost if a community decides to abandon completely the legacy developer forum. Goal: Adding to the body of evidence of existing research on best-answer prediction, here we show that, from a technical perspective, the content from existing developer forums might be automatically migrated to the Stack Overflow, although most of forums do not allow to mark a question as resolved, a distinctive feature of modern Q&A sites. Method: We trained a binary classifier with data from Stack Overflow and then tested it with data scraped from Docusign, a developer forum that has recently completed the move. Results: Our findings show that best answers can be predicted with a good accuracy, only relying on shallow linguistic (text) features, such as answer length and the number of sentences, combined with other features like answer upvotes and age, which can be easily computed in near real-time. Conclusions: Results provide an initial yet positive evidence towards the automatic migration of crowdsourced knowledge from legacy forums to modern Q&A sites.
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