CUED Publications database

Analysing information flows and key mediators through temporal centrality metrics

Tang, J and Musolesi, M and Mascolo, C and Latora, V and Nicosia, V (2010) Analysing information flows and key mediators through temporal centrality metrics. Proceedings of the 3rd Workshop on Social Network Systems, SNS'10.

Full text not available from this repository.

Abstract

The study of inuential members of human networks is an important research question in social network analysis. How- ever, the current state-of-the-art is based on static or ag- gregated representation of the network topology. We argue that dynamically evolving network topologies are inherent in many systems, including real online social and techno- logical networks: fortunately the nature of these systems is such that they allow the gathering of large quantities of fine- grained temporal data on interactions amongst the network members. In this paper we propose novel temporal centrality metrics which take into account such dynamic interactions over time. Using a real corporate email dataset we evaluate the impor- tant individuals selected by means of static and temporal analysis taking two perspectives: firstly, from a semantic level, we investigate their corporate role in the organisation; and secondly, from a dynamic process point of view, we mea- sure information dissemination and the role of information mediators. We find that temporal analysis provides a better understanding of dynamic processes and a more accurate identification of important people compared to traditional static methods. Copyright 2010 ACM.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:18
Last Modified: 13 Apr 2021 07:20
DOI: 10.1145/1852658.1852661