know the answer. For example, this person's friends might not have expertise in providing evaluations for a specific model of digital camera. Also asking the current wait time for security at the local airport might not be possible if none of this person's friends are currently at the airport. Nichols and Kang (2012) leveraged Twitter for question and answering with targeted strangers by taking advantage of its public accessibility. In their approach, they mined the public status updates posted on Twitter to find strangers with potentially useful information, and send questions to these strangers to collect responses. As a feasibility study, they collected information regarding response rate, and response time. 42% of users responded to questions from strangers, and 44% of the responses arrived within 30 minutes. Participation as a community Another important and unique component of social Q&A system is that it is a community which allows members to form relationships and bonds, so that their behavior in these social Q&A services will also add to their social capital. Gray et al. (2013) explored how bridging social capital, question type and relational closeness influence the perceived usefulness and satisfaction of information obtained through questions asked on Facebook. Their results indicated that bridging social capital could positively predict the perceived utility of the acquired information, meaning that information exchanges on social networks is an effective way of social capital conversion. Also, useful answers are more likely to be received from weak ties than strong ties. Authority detection in social media In order to recommend the most appropriate users to provide answers in a social network, we need to find approaches to detect users' authority in a social network. 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. 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. indegree (followers count) retweet count mention count An initial analysis of the three aforementioned metrics showed that the users with the highest indegrees and the users with the highest retweet/mention counts were not the same. The top 1% of users by indegree are shown to have very low correlation with the same percentile of users by retweets and by mentions. This implies that follower