Mendeley TY _ JOUR ID - 139506021734183210 TI - Analysis of expert finding algorithms in social network in order to rank the top algorithms JO - Journal of Information Systems and Telecommunication (JIST) JA - ES LA - en SN - 2322-1437 AU - kardan AhmadAgha AU - بزرگی بهنام AD - Assistant Professor AD - Amirkabir University of Technology Y1 - 2017 PY - 2017 VL - 20 IS - 5 SP - 217 EP - 224 KW - Expert-finding KW - Social Network Analysis KW - Question and answer community KW - Stack Overflow DO - N2 - The ubiquity of Internet and social networks have turned question and answer communities into an environment suitable for users to ask their questions about anything or to share their knowledge by providing answers to other users’ questions. These communities designed for knowledge-sharing aim to improve user knowledge, making it imperative to have a mechanism that can evaluate users’ knowledge level or in other words “to find experts”. There is a need for expert-finding algorithms in social networks or any other knowledge sharing environment like question and answer communities. There are various content analysis and link analysis methods for expert-finding in social networks. This paper aims to challenge four algorithms by applying them to our dataset and analyze the results in order to compare the algorithms. The algorithms suitable for expert finding has been found and ranked. Based on the results and tests it is concluded that the Z-score algorithm has a better performance than others. UR - rimag.ir/en/Article/14935 L1 - rimag.ir/en/Article/Download/14935 ER -