Predicting web searcher satisfaction with existing community-based answers

Abstract

Community-based Question Answering (CQA) sites, such as Yahoo! Answers, Baidu Knows, Naver, and Quora, have been rapidly growing in popularity. The resulting archives of posted answers to questions, in Yahoo! Answers alone, already exceed in size 1 billion, and are aggressively indexed by web search engines. In fact, a large number of search engine users benefit from these archives, by finding existing answers that address their own queries. This scenario poses new challenges and opportunities for both search engines and CQA sites. To this end, we formulate a new problem of predicting the satisfaction of web searchers with CQA answers. We analyze a large number of web searches that result in a visit to a popular CQA site, and identify unique characteristics of searcher satisfaction in this setting, namely, the effects of query clarity, query-to-question match, and answer quality. We then propose and evaluate several approaches to predicting searcher satisfaction that exploit these characteristics. To the best of our knowledge, this is the first attempt to predict and validate the usefulness of CQA archives for external searchers, rather than for the original askers. Our results suggest promising directions for improving and exploiting community question answering services in pursuit of satisfying even more Web search queries.

Characterizing Health-Related Community Question Answering

“…Figure 2a shows weekly Acute Respiratory Infection (ARI) rates for Russia from WHO/Europe influenza surveillance 3 against the share of documents with a high probability of the "flu" topic (the first column in Table 1). Figure 2b juxtaposes the weekly share of "runny nose" threads (the second column in Table 1) started by Moscow inhabitants vs. rainy days count in Russia"s capital 4 .…”

“…Community question answering (CQA) is one of the major destinations for health-related inquiries. Vast amounts of data collected by the CQA sites allow for re-using the "wisdom of crowds" [3]. Our study focuses on questions and answers on health and medicine.…”

Community Engagement and Quality Knowledge with Stackoverflow’s Reputation System: Applications to Bullipedia

“…Instead, most Q&A sites use collaborative voting mechanisms for users inside the community to evaluate and maintain high quality questions and answers (Tian et al 2013). By a quality answer, we mean the one that satisfies the asker (Liu et al 2008) and also other web users who will face similar problems in the future (Liu et al 2011 to traditional sources of information for programmers, like books, blogs, or other existing Q&A sites. The fact that both Atwood and Spolsky were popular bloggers contributed to its success in the early stages of the project as they brought their two communities of readers to their new site and generated the critical mass that made it work (Atwood 2008;Spolsky 2008).…”

Joint voting prediction for questions and answers in CQA

“…Different from these studies, our focus is to quantitatively verify the voting correlation between questions and answers. Other related work includes CQA site searcher satisfaction [16], potentially contributive user detection [17], question-answer matching [18], etc.…”