An Intelligent Approach for Extremism Detection Through Social Networks (For the English Language)

Abstract

Recent research indicates that extremist groups are excruciating using most social networking platforms on the Internet such as Twitter, Facebook, YouTube,......etc. to spread their ideologies and beliefs via inciting extremism and recruiting members through creating virtual online groups [1][2]. Social networking online extremism have attracted of artificial intelligence approaches, Machine Learning to classify and predict online extremism [3]. Several algorithms, techniques and approaches have been studied in the literature to counter, combat extremism and predict relevant events (table:01). In the present paper, we will highlight the problem of our research case study, the objectives to be achieved and the proposed research plan. It is within this category of applications and in the continuity of previous work that we wish to place our position, Develop the necessary features to identify negative and positive evaluations on the social web. Specifically, we are interested in characterizing the words, describing the extreme words and expressions that are expressed from a collection of comments and tweets on social networks on the web