The rise of social media provides a great opportunity for people to reach out to their social connections to satisfy their information needs. However, generic social media platforms are not explicitly designed to assist information seeking of users. In this paper, we propose a novel framework to identify the social connections of a user able to satisfy his information needs. The information need of a social media user is subjective and personal, and we investigate the utility of his social context to identify people able to satisfy it. We present questions users post on Twitter as instances of information seeking activities in social media. We infer soft community memberships of the asker and his social connections by integrating network and content information. Drawing concepts from the social foci theory, we identify answerers who share communities with the asker w.r.t. the question. Our experiments demonstrate that the framework is effective in identifying answerers to social media questions.
Social media questions have received considerable attention in research communities @cite_8 @cite_35 @cite_37 . An analytical study on questions asked and the answers received in Twitter is presented in @cite_25 @cite_20 . They indicated that subjective questions were the most prevalent and the trust users have on their friends was the primary factor for asking questions. A study of questions and responses received in Facebook was conducted in @cite_6 @cite_23 and bridging social capital was proposed to be a strong motivation for Q &A activity in social media. These works give interesting insights to the question answering process in social media, but do not focus on identifying answerers to these questions.
@cite_35 @cite_37 @cite_8 @cite_6 @cite_23 @cite_25 @cite_20
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Research has identified a link between Facebook use and bridging social capital, which speaks to the informational resources provided by a diverse network of connections. In order to explicate the mechanism through which Facebook may help individuals mobilize these embedded informational and support resources, this study explores the role of bridging social capital, question type, and relational closeness on the perceived utility and satisfaction of information obtained through questions posed to one's network of Facebook Friends through the status update feature. Employing a mixed-method approach, we utilize survey data collected from a sample of non-academic university staff (N=666), as well as actual Facebook question examples and responses collected during a follow-up lab session from a subset of this sample (N=71). Results indicate that question-askers' bridging social capital positively predicts the utility of responses received on SNS, while useful responses are more likely to be received from weaker ties. People often turn to their social networks to fulfill their information needs. We conducted a study of question asking and answering (QA 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. We provide a rich characterization of Q&A in social information streams and discuss implications for design. Social media provides a platform for seeking information from a large user base. Information seeking in social media, however, occurs simultaneously with users expressing their viewpoints by making statements. Rhetorical questions have the form of a question but serve the function of a statement and might mislead platforms assisting information seeking in social media. It becomes difficult to identify rhetorical questions as they are not syntactically different from other questions. In this paper, we develop a framework to identify rhetorical questions by modeling the motivations of the users to post them. We focus on one motivation of the users drawing from linguistic theories, to implicitly convey a message. We develop a framework from this motivation to identify rhetorical questions in social media and evaluate the framework using questions posted on Twitter. This is the first framework to model the motivations for posting rhetorical questions to identify them on social Social media is being increasingly used to request information and help in situations like natural disasters, where time is a critical commodity. However, generic social media platforms are not explicitly designed for timely information seeking, making it difficult for users to obtain prompt responses. Algorithms to ensure prompt responders for questions in social media have to understand the factors affecting their response time. In this paper, we draw from sociological studies on information seeking and organizational behavior to model the future availability and past response behavior of the candidate responders. We integrate these criteria with their interests to identify users who can provide timely and relevant responses to questions posted in social media. We propose a learning algorithm to derive optimal rankings of responders for a given question. We present questions posted on Twitter as a form of information seeking activity in social media. Our experiments demonstrate that the proposed framework is useful in identifying timely and relevant responders for questions in social media.