An Application of Random Walk on Fake Account Detection Problem: A Hybrid Approach
Abstract
Social networks play a significant role in today's world. The importance of social networks, for example Facebook or Twitter, are undeniable. However, they also have many issues. One of which is the need for a defense mechanism against fake accounts. It is obviously not a trivial task to separate fake accounts from authentic ones. In this paper, we propose a ranking scheme, comprising of both graph based and feature based approaches to aid the detection of fake Facebook profiles. Utilizing Support Vector Machine (SVM) cortes1995 and SybilWalk JWZ17, the model achieved high accuracy over the set of ten thousands Vietnamese Facebook accounts.
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.