publication . Article . Preprint . 2015

Combating Fraud in Online Social Networks: Detecting Stealthy Facebook Like Farms

Ikram Muhammad;
  • Published: 01 Jun 2015
Abstract
As businesses increasingly rely on social networking sites to engage with their customers, it is crucial to understand and counter reputation manipulation activities, including fraudulently boosting the number of Facebook page likes using like farms. To this end, several fraud detection algorithms have been proposed and some deployed by Facebook that use graph co-clustering to distinguish between genuine likes and those generated by farm-controlled profiles. However, as we show in this paper, these tools do not work well with stealthy farms whose users spread likes over longer timespans and like popular pages, aiming to mimic regular users. We present an empiric...
Subjects
free text keywords: Computer Science - Social and Information Networks, Computer Science - Cryptography and Security

1. A. Andoni and P. Indyk. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. Commun. ACM, 2008. [OpenAIRE]

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publication . Article . Preprint . 2015

Combating Fraud in Online Social Networks: Detecting Stealthy Facebook Like Farms

Ikram Muhammad;