Experts and likely to be closed discussions in question and answer communities: An analytical overview
作者：
Highlights：
• Experts gained their status mainly by providing help rather than asking for it.
• The weighted sum better quantifies the reputation of an expert member.
• The inclusion of an expert in a discussion was found to result in longer debates.
• Machine Learning and users' behavior identified likely to be closed discussions and experts.
• Semantic annotations are helpful to find and recommend a topical expert.
摘要
•Experts gained their status mainly by providing help rather than asking for it.•The weighted sum better quantifies the reputation of an expert member.•The inclusion of an expert in a discussion was found to result in longer debates.•Machine Learning and users' behavior identified likely to be closed discussions and experts.•Semantic annotations are helpful to find and recommend a topical expert.
论文关键词：Q&A community analysis,Expert behavior,Likely to be closed discussions,Interaction analysis,Graph analysis,Topical experts
论文评审过程：Received 8 March 2017, Accepted 3 June 2018, Available online 6 June 2018, Version of Record 18 January 2019.
论文官网地址：https://doi.org/10.1016/j.chb.2018.06.004
