Toward free spam social networks: detecting and tracking spammers in Twitter

Mahdi Washha (1) , Florence Sèdes (1)

1 IRIT-SIG - Systèmes d’Informations Généralisées

Social networks are now so well established with playing an important role at communication level between people. However, the propagation of noisy information, so-called ”spam”, in social networks is growing up daily at unusual rates where unethical goals stand behind publishing spam information. The spreading of spam affects negatively in different aspects, summarized in : (i) polluting real-time search ; (ii) interfering on statistics compu- ted by mining tools ; (iii) consuming significant resources from both humans and systems ; (iv) decreasing the performance of search engines that use explicitly social signals ; and (v) violating the privacy of user’s which occurs because of viruses and phishing methods. Thus, this research aims at finding out solutions suitable for the applications that take social networks as a source of information. Also, we target to overcome the existing limitations in the current state of art solutions.

Mots clés: Time; Machine Learning; Legitimate Users; Spam; Social Networks; Réseaux Sociaux; Utilisateurs Légitimes; Temps Social Networks

Mots clés: Temps; Machine Learning; Utilisateurs Légitimes; Réseaux Sociaux; Spam

Domaines: Informatique [cs]

Mahdi Washha, Florence Sèdes. Toward free spam social networks: detecting and tracking spammers in Twitter. 8ème édition du Forum Jeunes Chercheurs du congrès INFORSID (INFORSID 2016), May 2016, Grenoble, France. pp.33-36, ⟨10.13140/RG.2.2.26504.21763⟩. ⟨hal-03159075⟩