Empirical Study on Overlapping Community Detection in Question and Answer Sites - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Empirical Study on Overlapping Community Detection in Question and Answer Sites

Résumé

In many social networks, people interact based on their interests. Community detection algorithms are then useful to reveal the sub-structures of a network and help us find interest groups. Identifying these social communities can bring benefit to understanding and predicting users behaviors. However, for some kind of online community sites such as question-and-answer (Q&A) sites or forums, there is no friendship based social network structure, which means people are not aware who they are in contact with. Therefore, many traditional community detection techniques do not apply directly. In this paper, we propose an empirical approach for extracting data from Q&A sites suitable to apply community detection methods. Then we compare three kinds of community detection methods we applied on a dataset extracted from the popular Q&A site StackOverflow. We analyze and comment the results of each method.
Fichier principal
Vignette du fichier
asonam2014.pdf (489.6 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01075944 , version 1 (12-07-2016)

Identifiants

Citer

Zide Meng, Fabien Gandon, Catherine Faron Zucker, Ge Song. Empirical Study on Overlapping Community Detection in Question and Answer Sites. Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on, Aug 2014, Beijing, China. ⟨10.1109/ASONAM.2014.6921608⟩. ⟨hal-01075944⟩
239 Consultations
181 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More