Conference proceeding
Who will be participating next?: predicting the participation of Dark Web community
Proceedings of the ACM SIGKDD Workshop on intelligence and security informatics, pp 1-7
12 Aug 2012
Abstract
Predicting whether a user will be participating in a thread has broad applications, such as thread recommendation and ranking. In an extremist forum, knowing which user will be interested to join a particular thread with sensitive or threatening information is also important for security agent to prevent or prepare for any potential outbreak of crisis. Traditional methods employed a bipartite graph to represent user-thread relationships and predict potential users for a new coming thread based on user similarities. In this paper, we propose a User Interest and Topic Detection model to extract topics and trends from a document corpus and also discover users' interests toward these trends. Information of user interest is then used to predict potential information consumers for a given thread. Experiments conducted in the Dark Web dataset showed the effectiveness of our approach; especially when we have limited information about who have already participated in an existing new thread.
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11 citations in Scopus
Details
- Title
- Who will be participating next?
- Creators
- Xuning Tang - Drexel UniversityChristopher Yang - Drexel UniversityMi Zhang - Drexel University
- Publication Details
- Proceedings of the ACM SIGKDD Workshop on intelligence and security informatics, pp 1-7
- Conference
- ACM SIGKDD Workshop on intelligence and security informatics
- Series
- ISI-KDD '12
- Publisher
- Association for Computing Machinery (ACM)
- Number of pages
- 1
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Scopus ID
- 2-s2.0-84864998665
- Other Identifier
- 991019173963704721