N. Derbas, F. Segond, Muntsa Padró, Emmanuelle Dusserre, Teodora Dobre, S. Monaci, Gustavo Mastrobuoni
{"title":"Semantic Analysis Supporting De-Radicalisation","authors":"N. Derbas, F. Segond, Muntsa Padró, Emmanuelle Dusserre, Teodora Dobre, S. Monaci, Gustavo Mastrobuoni","doi":"10.1109/DEXA.2017.20","DOIUrl":null,"url":null,"abstract":"Internet and Social media are widely used by terrorist organizations to spread their ideas and recruit foreign fighters. The aim of SAFFRON project is to build a system able to support early detection of foreign fighters' recruitment by terrorist groups in Europe. It consists in studying recruitment communication strategies on social media (e.g. narrations, argumentative tropes and myths used), and their evolution in time, as well as in identifying needs, values, cultural and social contexts of the target groups (young foreign fighters). In this paper, we will describe Safapp, the application developed to support semantic analysis of social network. We focus on how SAFFRON makes use of natural language processing and machine learning to categorize and analyse messages dealing with recruitment and radicalization on social networks.","PeriodicalId":127009,"journal":{"name":"2017 28th International Workshop on Database and Expert Systems Applications (DEXA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 28th International Workshop on Database and Expert Systems Applications (DEXA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEXA.2017.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Internet and Social media are widely used by terrorist organizations to spread their ideas and recruit foreign fighters. The aim of SAFFRON project is to build a system able to support early detection of foreign fighters' recruitment by terrorist groups in Europe. It consists in studying recruitment communication strategies on social media (e.g. narrations, argumentative tropes and myths used), and their evolution in time, as well as in identifying needs, values, cultural and social contexts of the target groups (young foreign fighters). In this paper, we will describe Safapp, the application developed to support semantic analysis of social network. We focus on how SAFFRON makes use of natural language processing and machine learning to categorize and analyse messages dealing with recruitment and radicalization on social networks.