tools that could combine the speed and breadth of traditional search engines with the trustworthiness, personalization, and the high engagement of social media Q&A. Paul et al. (2011) did a study on question and answering on Twitter, and found that out of the 1152 questions they examined, the most popular question types asked on Twitter were rhetorical (42%) and factual (16%). Surprisingly, along with entertainment (29%) and technology (29%) questions, people asked personal and health-related questions (11%). Only 18.7% questions received response, while a handful of questions received a high number of responses. The larger the askers’ network, the more responses she received; however, posting more tweets or posting more frequently did not increase chances of receiving a response. Most often the “follow” relationship between asker and answerer was one-way. Paul et al. also examined what factors of the askers would increase the chance of getting a response and found that more relevant responses are received when there is a mutual relationship between askers and answerers. Intuitively, we would expect this, as mutual relationship would indicate stronger tie strength and hence, more number of relevant answers. Social Q&A services Existing social Q&A services can be characterized from the three perspectives, by the definition of social Q&A as a service involving (1) a method for presenting information needs, (2) a place for responding to information need, and (3) participation as a community. Presenting information needs These social networks support various friendsourcing behavior, provide information benefits that oftentimes traditional search tools cannot, and also may reinforce social bonds through the process. However, there are many questions and limitations that may prevent people from asking questions on their social networks. For example, they may feel uncomfortable asking questions that are too private, might not want to cost too much other people's time and effort, or might feel the burden of social debts. Rzeszotarski and Morris (2014) took a novel approach to explore the perceived social costs of friendsourcing on Twitter via monetary choices. They modeled friendsourcing costs across users, and compared it with crowdsourcing on Amazon Mechanical Turk. Their findings suggested interesting design considerations for minimizing social cost by building a hybrid system combining friendsourcing and crowdsourcing with microtask markets. Responding to information needs Sometimes, only asking question from people's own social networks or friends is not enough. If the question is obscure or time sensitive, no members of their social networks may