Skip to Main content Skip to Navigation
Conference papers

Classification of Message Spreading in a Heterogeneous Social Network

Abstract : Nowadays, social networks such as Twitter, Facebook and LinkedIn become increasingly popular. In fact, they introduced new habits, new ways of communication and they collect every day several information that have different sources. Most existing research works fo-cus on the analysis of homogeneous social networks, i.e. we have a single type of node and link in the network. However, in the real world, social networks offer several types of nodes and links. Hence, with a view to preserve as much information as possible, it is important to consider so-cial networks as heterogeneous and uncertain. The goal of our paper is to classify the social message based on its spreading in the network and the theory of belief functions. The proposed classifier interprets the spread of messages on the network, crossed paths and types of links. We tested our classifier on a real word network that we collected from Twitter, and our experiments show the performance of our belief classifier.
Complete list of metadatas

Cited literature [21 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01108020
Contributor : Arnaud Martin <>
Submitted on : Thursday, January 22, 2015 - 9:29:36 AM
Last modification on : Friday, March 6, 2020 - 4:10:02 PM
Document(s) archivé(s) le : Thursday, April 23, 2015 - 10:11:22 AM

Files

articleIPMUV04.pdf
Files produced by the author(s)

Identifiers

Citation

Siwar Jendoubi, Arnaud Martin, Ludovic Liétard, Boutheina Ben Yaghlane. Classification of Message Spreading in a Heterogeneous Social Network. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), Jul 2014, Montpellier, France. pp.66 - 75, ⟨10.1007/978-3-319-08855-6_8⟩. ⟨hal-01108020⟩

Share

Metrics

Record views

415

Files downloads

315