Proceedings of the 11th international conference on World Wide Web
Parallel crawling for online social networks
Proceedings of the 16th international conference on World Wide Web
Examining privacy and disclosure in a social networking community
Proceedings of the 3rd symposium on Usable privacy and security
Who's really in your top 8: network security in the age of social networking
Proceedings of the 35th annual ACM SIGUCCS fall conference
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
Prying Data out of a Social Network
ASONAM '09 Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining
APWEB '10 Proceedings of the 2010 12th International Asia-Pacific Web Conference
Imagined communities: awareness, information sharing, and privacy on the facebook
PET'06 Proceedings of the 6th international conference on Privacy Enhancing Technologies
KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
Multi agent system approach for vulnerability analysis of online social network profiles over time
International Journal of Knowledge and Web Intelligence
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Nowadays, we witness a flood of continuously changing information from a variety of web sources. The desire to track the information changes in real time requires new methods in web information retrieval. This paper explores the process of retrieving information from Online Social Networks (OSNs) using Multi Agent System (MAS) technology. The novelty of this study consists in leaving an agent in each user profile to monitor its updates which are sent to a controller agent that saves a history of each user's activity in a local repository. An algorithm making use of MAS within the Online Social Network Retrieval System (OSNRS) is proposed. Our experimental work shows that using MAS simplifies the process of tracking profile's history and opens the opportunity of understanding the dynamic behavior of OSN users especially when it is combined with text mining.