Learning natural ordering of tags in domain-specificQ&Asites

Abstract

Tagging is a defining characteristic of Web 2.0. It allows users of social computing systems (e.g., question and answering (Q&A) sites) to use free terms to annotate content. However, is tagging really a free action? Existing work has shown that users can develop implicit consensus about what tags best describe the content in an online community. However, there has been no work studying the regularities in how users order tags during tagging. In this paper, we focus on the natural ordering of tags in domain-specific Q&A sites. We study tag sequences of millions of questions in four Q&A sites, i.e., CodeProject, SegmentFault, Biostars, and CareerCup. Our results show that users of these Q&A sites can develop implicit consensus about in which order they should assign tags to questions. We study the relationships between tags that can explain the emergence of natural ordering of tags. Our study opens the path to improve existing tag recommendation and Q&A site navigation by leveraging the natural ordering of tags.

Keywords

Question and answering (Q&A) sites / Tagging / Natural order / Skip gram

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2021 Zhejiang University Press