Abstract: The recent popularity of social media is changing the way people share and acquire knowledge. Companies started using intra-organizational social media applications in order to improve the communication and collaboration among employees. In addition to their professional use, people have been using these sites in their personal lives for information acquisition purposes, such as community question answering sites for their questions. In such environments the interactions do not always occur between users who know each other well enough to assess expertise of one another or trust the accuracy of their created content. This talk addresses this problem by estimating topic specific expertise scores of users which can be also used to improve the expertise related applications in social media. Three types of information: (1) user created content, (2) underlying social network structure and (3) the available timestamps will be exploited in this talk and both effective and efficient approaches will be described as well.

 

Bio: Dr. Reyyan Yeniterzi is an assistant professor at Ozyegin University, Department of Computer Science. She obtained her B.Sc. and M.Sc from Sabanci University, Department of Computer Science and Engineering in 2007 and 2009, M.Sc. and Ph.D. from School of Computer Science at Carnegie Mellon University in 2012 and 2015. During her studies, in addition to Microsoft Turkey and Google, she also worked as a research visitor at the International Computer Science Institute (ICSI), Vanderbilt and Qatar Carnegie Mellon Universities. Her research interests include but not limited to Natural Language Processing, Text Mining, Information Retrieval, Social Media Analysis and Machine Translation.