Abstract
In this paper, we propose a new role analyzing paradigm for social networks enlightened by topic modeling, which can be adopted as a primitive building block in various security related tasks, such as hidden community finding, important person recognizing and so on. We first present the social network under analyzing as a heterogeneous network constructed by both the users and the subjects discussed among them. We then view this network in a Bag-of-Users schema, which mimics its classical Bag-of-Words counterpart. In this schema, the subjects discussed are treated as 'documents' while the users are treated as 'words' which construct the 'documents'. Based on this novel presentation, we finally apply topic modeling technology to perform the social role clustering. Experiments on a practical security-related social network dataset prove the effectiveness of our approach.
Original language | English (US) |
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Title of host publication | IEEE International Conference on Intelligence and Security Informatics |
Subtitle of host publication | Cybersecurity and Big Data, ISI 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 211-213 |
Number of pages | 3 |
ISBN (Electronic) | 9781509038657 |
DOIs | |
State | Published - Nov 15 2016 |
Event | 14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015 - Tucson, United States Duration: Sep 28 2016 → Sep 30 2016 |
Other
Other | 14th IEEE International Conference on Intelligence and Security Informatics, ISI 2015 |
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Country | United States |
City | Tucson |
Period | 9/28/16 → 9/30/16 |
Keywords
- hidden community
- network structure mining
- social network
- social role
- topic model
ASJC Scopus subject areas
- Information Systems
- Artificial Intelligence
- Computer Networks and Communications
- Information Systems and Management
- Safety, Risk, Reliability and Quality