A Comprehensive Survey and Classification of Approaches for Community Question Answering

Abstract

Community question-answering (CQA) systems, such as Yahoo! Answers or Stack Overflow, belong to a prominent group of successful and popular Web 2.0 applications, which are used every day by millions of users to find an answer on complex, subjective, or context-dependent questions. In order to obtain answers effectively, CQA systems should optimally harness collective intelligence of the whole online community, which will be impossible without appropriate collaboration support provided by information technologies. Therefore, CQA became an interesting and promising subject of research in computer science and now we can gather the results of 10 years of research. Nevertheless, in spite of the increasing number of publications emerging each year, so far the research on CQA systems has missed a comprehensive state-of-the-art survey. We attempt to fill this gap by a review of 265 articles published between 2005 and 2014, which were selected from major conferences and journals. According to this evaluation, at first we propose a framework that defines descriptive attributes of CQA approaches. Second, we introduce a classification of all approaches with respect to problems they are aimed to solve. The classification is consequently employed in a review of a significant number of representative approaches, which are described by means of attributes from the descriptive framework. As a part of the survey, we also depict the current trends as well as highlight the areas that require further attention from the research community.

Public health and social media: A study of Zika virus‐related posts on Yahoo! Answers

“…All health-related questions/ answers usually have been regarded as health information needs. Answers for this study because it was considered to be one of the most important public Q&A platforms in terms of its coverage, public visibility, and quality (Srba & Bielikova, 2016). In addition, a framework for modeling health information needs containing types of information and a taxonomy for underlying user intent containing have been developed (Chen, Zhang, & Mark, 2012, April;Oh, 2015;Oh et al, 2012).…”

“…Answers (2017) because it is regarded as one of the most important and widely used public social Q&A websites (Srba & Bielikova, 2016). Answers (2017) because it is regarded as one of the most important and widely used public social Q&A websites (Srba & Bielikova, 2016).…”

“…We selected Yahoo! Answers for this study because it was considered to be one of the most important public Q&A platforms in terms of its coverage, public visibility, and quality (Srba & Bielikova, 2016).…”

Duplicate Question Detection in Stack Overflow: A Reproducibility Study

“…We refer the reader to the comprehensive survey by Srba and Bielikova on Q&A websites [25]. The most closely related work includes techniques to retrieve similar questions and question classification.…”

Different Facets of Text Based Automated Question Answering System

“…The ranking metric network learning framework has integrated users' relative quality rank to given questions and their social relations for expert identification. Srba et al, [31]has reviewed 265 articles published between 2005 and 2014 related to Community question-answering (CQA) and presented a comprehensive state-of-the-art survey. They have proposed a framework that defines descriptive attributes of CQA approaches and their classification with respect to problems they are aimed to solve.…”