Analysis of expert finding algorithms in social network in order to rank the top algorithms

The ubiquity of the 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”. Experts are people who are highly talented in a specific field like technology, languages, cooking and etc, and we focused on specific fields in programming languages. There is a need for expert-finding algorithms in social networks or any other knowledge sharing environment like question and answer communities. So companies that looking for hiring programmers can easily find people suit their needs. There are various content analysis and link analysis methods for expert-finding in social networks. Experts can be identified by their behaviors in forums and their relationships in proportion to the questions and answers they share. Therefore, analyzing social networks can provide us with appropriate information. 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. The outcome of this article for enthusiasts is top algorithms for expert finding in question-answer communities. In this paper, first, we will start by introducing the problem of expert finding problem the related works will be presented then algorithms and dataset are introduced and finally results are illustrated.