Biblio
Filters: Author is Eom, Chris Soo-Hyun [Clear All Filters]
.
2016. Spammer Detection for Real-time Big Data Graphs. Proceedings of the Sixth International Conference on Emerging Databases: Technologies, Applications, and Theory. :51–60.
In recent years, prodigious explosion of social network services may trigger new business models. However, it has negative aspects such as personal information spill or spamming, as well. Amongst conventional spam detection approaches, the studies which are based on vertex degrees or Local Clustering Coefficient have been caused false positive results so that normal vertices can be specified as spammers. In this paper, we propose a novel approach by employing the circuit structure in the social networks, which demonstrates the advantages of our work through the experiment.