Title
Communication overload management through social interactions clustering
Date Issued
04 April 2016
Access level
open access
Resource Type
conference paper
Author(s)
LOSSIO VENTURA, JUAN ANTONIO DE JESUS
Hacid H.
Roche M.
Poncelet P.
University of Montpellier
Publisher(s)
Association for Computing Machinery
Abstract
We propose in this paper to handle the problem of overload in social interactions by grouping messages according to three important dimensions: (i) content (textual and hashtags), (ii) users, and (iii) time difference. We evaluated our approach on a Twitter data set and we compared it to other existing approaches and the results are promising and encouraging.
Start page
1166
End page
1169
Volume
April August 04
Language
English
OCDE Knowledge area
Ciencias de la información Medios de comunicación, Comunicación socio-cultural
Subjects
DOI
10.1145/2851613.2851984
Scopus EID
2-s2.0-84975819733
Resource of which it is part
Proceedings of the ACM Symposium on Applied Computing
ISBN of the container
978-145033739-7
Conference
31st Annual ACM Symposium on Applied Computing, SAC 2016
Sponsor(s)
ACM Special Interest Group on Applied Computing (SIGAPP)
Sources of information: Directorio de Producción Científica Scopus