Prominent Users Detection during Specific Events by Learning On- and Off-topic Features of User Activities

Imen Bizid (1) , Nibal Nayef (1) , Patrice Boursier (1) , Sami Faiz (2) , Jacques Morcos (1)

1 L3I - Laboratoire Informatique, Image et Interaction - EA 2118
2 UMA - Université de la Manouba [Tunisie]

Microblogs such as Twitter are characterized by the richness and recency of information shared by their users during major events. However, it is very challenging to automatically mine for information or for users sharing certain information due to the huge variety of unstructured stream of data shared in such microblogs. This work proposes a ranking and classification model for identifying users sharing useful information during a specified event. The model is based on a novel set of features that can be computed in real time. These features are designed such that they take into account both the on and off-topic activities of a user. Once users are characterized by a feature vector, supervised machine learning tool is trained to classify users as either prominent or not. Our model has been tested on data shared during a flooding disaster event and performed very well. The achieved results show the effectiveness of the proposed model for both the classification and ranking of prominent users in such events, and also the importance of the adjustment of the on-topic features by the off-topic ones when describing users' activities.

Mots clés: Key user identification; On-and off-topic features; Events in Twitter; SVM Classification and Ranking; Real-time feature computation

Domaines: Réseaux sociaux et d'information [cs.SI]; Recherche d'information [cs.IR]

Imen Bizid, Nibal Nayef, Patrice Boursier, Sami Faiz, Jacques Morcos. Prominent Users Detection during Specific Events by Learning On- and Off-topic Features of User Activities. The 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining ASONAM 2015, Aug 2015, Paris, France. pp.500-503, ⟨10.1145/2808797.2809411⟩. ⟨hal-01287163⟩