FCA for Common Interest Communities discovering

Major scientific and industrial issues related to social networks have led many researchers to focus on the long-standing problem of automatic communities extraction. The vast majority of the proposed methods tend to make a partition of the entities from the initial graph of observed relationships. The semantics of these relationships is rarely considered. The lack of information about the elements that connect or repel individuals course, is the main cause. In this article, we focus our interest on the detection of Common Interest Communities (CIC) in social networks. In this respect, we introduce a new approach called SOC Miner for communities detection based on the use of both Formal Concept Analysis (FCA) techniques and data from social networks. Carried out experiments over real-world data sets emphasize the relevance of our proposal and open many issues.