Citation

Can We Trust Social Media Data? Social Network Manipulation by an IoT Botnet

Author:
Paquet-Clouston, Masarah; Bilodeau, Olivier; Décary-Hétu, David
Year:
2017

The size of a social media account's audience -- in terms of followers or friends count -- is believed to be a good measure of its influence and popularity. To gain quick artificial popularity on online social networks (OSN), one can buy likes, follows and views, from social media fraud (SMF) services. SMF is the generation of likes, follows and views on OSN such as Facebook, Twitter, YouTube, and Instagram. Using a research method that combines computer sciences and social sciences, this paper provides a deeper understanding of the illicit market for SMF. It conducts a market price analysis for SMF, describes the operations of a supplier -- an Internet of things (IoT) botnet performing SMF -- and provides a profile of the potential customers of such fraud. The paper explains how an IoT botnet conducts social network manipulation and illustrates that the fraud is driven by OSN users, mainly entertainers, small online shops and private users. It also illustrates that OSN strategy to suspend fake accounts only cleans the networks a posteriori of the fraud and does not deter the crime -- the botnet -- or the fraud -- SMF -- from happening. Several solutions to deter the fraud are provided.