Context based Expert Finding in Online Communities using Social Network Analysis

Nowadays, online communities are one of the most popular collaborative environments in the Internet where people are free to express their opinions. These communities provide facilities for knowledge sharing in which, people can share their experience with each other. The main problem regarding to the knowledge sharing on online communities is the wide range of information on them without any mechanism to determine their validity. So, for knowledge seekers, it is important to recognize the expertise of each member based on contexts to find the best answers among all replies to his question. Although, lots of researches have been conducted so far to determine the level of people’s expertise, none of them has had context based approach to the problem. In this research a novel method based on social network analysis is proposed to find the experts in different contexts. For evaluation process of the proposed method, Metafilter Forum was chosen and the data has been processed in several steps. First, data were gathered by our crawling program and then extracted, transformed and loaded to data base by ETL operations. Then, experts on specified context were found by applying the proposed method on the processed data. Finally, accuracy of the method was calculated and compared with other methods.