With the advancement of Web 2.0 techniques, social question and answering has become a new venue for individuals to seek for information online. Although it has been investigated by a number of works lately, so far still little has been known about how people interact with each other in order to satisfy their information needs in social Q&A. With the aim to understand the patterns of user interactions in the social Q&A context, as well as factors that may affect such kind of back-and-forth communications, in this work we collect over 1,000 question and answering dialogues from Sina Weibo. Statistical analyses including ANOVA, Pearson's correlation, linear regression and independent t-test are performed in order to answer our proposed research questions. Our results demonstrate the importance of studying the interactions in social Q&A given that about half of our collected question-answer pairs are of interactive nature. From the quantity perspective, we observe that questions within more complicated topics, such as "Healthcare" and "Education" generate more interactions. Significantly positive correlation is also noticed between social tie strength and the number of interactions. By manually annotating all interactive answers, we also indicate the importance of weak ties in providing high quality answers and interactions. Based on our results, we proposed potential implications for future design and implementations.
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