Abstract
In many video social networks, including YouTube, users are permitted to post video responses to other users’ videos. Such a response can be legitimate or can be a video response spam, which is a video response whose content is not related to the topic being discussed. Malicious users may post video response spam for several reasons, including increase the popularity of a video, marketing advertisements, distribute pornography, or simply pollute the system.
In this paper we consider the problem of detecting video spammers. We first construct a large test collection of YouTube users, and manually classify them as either legitimate users or spammers. We then devise a number of attributes of video users and their social behavior which could potentially be used to detect spammers. Employing these attributes, we apply machine learning to provide a heuristic for classifying an arbitrary video as either legitimate or spam. The machine learning algorithm is trained with our test collection. We then show that our approach succeeds at detecting much of the spam while only falsely classifying a small percentage of the legitimate videos as spam. Our results highlight the most important attributes for video response spam detection.
Benevenuto, Fabricio, Tiago Rodrigues, Virgilio Almeida, Jussara Almeida, Chao Zhang, and Keith Ross.
Identifying Video Spammers in Online Social Networks.
In Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web, Beijing, China, 22 April 2008.
Also see:
Benevenuto, F., Rodrigues, T., Almeida, V., Almeida, J., and Gonçalves, M. Detecting Spammers and Content Promoters in Online Video Social Networks. In Proceedings of the 32nd international ACM SIGIR Conference on Research and Development in information Retrieval (Boston, MA, USA, July 19 – 23, 2009).
Related posts:
- Characterizing Video Responses in Social Networks. body {background-repeat: no-repeat;}Abstract Video sharing sites, such as YouTube, use...
- Measurement and Analysis of Online Social Networks. body {background-repeat: no-repeat;}Abstract Online social networking sites like Orkut, YouTube,...
- Profiling Social Networks: A Social Tagging Perspective. body {background-repeat: no-repeat;}Ding, Ying, Elin K. Jacob, James Caverlee, Michael...
- The Digital Difference of Online Social Networking in the Caribbean. body {background-repeat: no-repeat;}Abstract Users of online social networking sites have...
- Exploring Social Dynamics in Online Media Sharing. body {background-repeat: no-repeat;}Abstract It is now feasible to view media...
Related posts brought to you by Yet Another Related Posts Plugin.
