[1] Social information seeking is often materialized in online question-answering (QA) websites, which are driven by a community.
Such QA sites have emerged in the past few years as an enormous market, so to speak, for the fulfillment of information needs.
cQA sites make their content – questions and associated answers submitted on the site – available on the open web, and indexable by search engines, thus enabling web users to find answers provided for previously asked questions in response to new queries.
Viewed in that light, online communities have performed a question answering function perhaps since the advent of Usenet and Bulletin Board Systems, so in one sense cQA is nothing new.
Despite this short history, however, cQA has already attracted a great deal of attention from researchers investigating information seeking behaviors,[5] selection of resources,[6] social annotations,[7] user motivations,[8] comparisons with other types of question answering services,[9] and a range of other information-related behaviors.
They found that half (50.6%) of respondents reported having used their status messages to ask a question, which indicated that Q&A on social networks is popular.
Only a very small portion (6.5%) of the questions were answered, but the 89.3% of the respondents were satisfied with the response time they experienced even though there's a discrepancy between that and expectation.
Rzeszotarski and Morris (2014)[15] took a novel approach to explore the perceived social costs of friendsourcing on Twitter via monetary choices.
Their findings suggested interesting design considerations for minimizing social cost by building a hybrid system combining friendsourcing and crowdsourcing with microtask markets.
Nichols and Kang (2012)[16] leveraged Twitter for question and answering with targeted strangers by taking advantage of its public accessibility.
In the field of information retrieval, there has been a trend of research investigating ways to detect users' authority effectively and accurately in a social network.
Cha et al.[18] investigate possible metrics for determining authority users on popular social network Twitter.
They propose the following three simple network-based metrics and discuss their usefulness in determining a user's influence.