Abstract
Online communities are the most popular interactive environments on the Internet, which provide users with a platform to share their knowledge and expertise. The most important use of online communities in cyberspace is sharing knowledge. These communities are a great place to ask questions and find answers. The important challenges of these communities are the large volume of information and the lack of a method to determine their validity as well as expert finding which attracted a lot of attention in both industry and academia in. Therefore, identifying persons with relevant knowledge on a given topic and ranking them according to their expertise score can help to calculate the accuracy of the comments submitted on the internet. In this research, a model for finding experts and determining their domain expertise level by the aid of statistical calculations and the ant colony algorithm in the MetaFilter online community was presented. The WordNet Dictionary was used to determine the relevance of the user’s questions with the intended domain. The proposed algorithm determines the level of people’s expertise in the intended field by using the pheromone section of the Ant colony algorithm, which is based on the similarity of the questions sent by the users and the shared knowledge of the users from their interactions in the online community
Highlights
Online communities are among the most important achievements of Web 2.0 technologies that have been noticed by researchers and business organizations due to their large volume of valuable raw data [1]
Phase IV: Implementing the Ant Colony Algorithm. At this phase, inspired by the pheromone part of the ant colony algorithm, users are treated as a route, questions are considered as ants, the level of attraction between people in the specialized network is treated as the information, and knowledge share of users in each question is considered as pheromone
The results of the proposed Expertise AntRank (EAR) method were compared with other methods like Indegree, Z-degree, Z-number, AnswerNum, ExpertiseRank, and SNPageRank in three different domains of internet, travel and music
Summary
Online communities are among the most important achievements of Web 2.0 technologies that have been noticed by researchers and business organizations due to their large volume of valuable raw data [1]. The important issue is finding the level of expertise of people in different fields as well as the level of users’ trust in experts to use their answers in various issues ’[2]. Journal of Information Systems and Telecommunication, Vol 8, No 2, April-June 2020 considered and there is no difference between the answers given to people with different levels of expertise, while the knowledge of a person responding to an expert user is different from that of a user responding to a beginner [8]. For the first time in this field, using the Ant colony algorithm and considering the quality of communications and users’ trust and reputation, a new model is proposed, which is a good solution to solve problems and challenges of online communities with high accuracy The research literature is reviewed first; the research method and the proposed algorithm are presented. The conclusion and recommendations for future studies are expressed
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