How “VKontakte” fake accounts influence the social network of users

© Springer Nature Switzerland AG 2018. In this paper, the problem of fake accounts in online social networks is addressed through the lens of resulting misstatements of the structure of network interactions between users. The study of a network as a social space becomes difficult because of additional noise created by fakes. The aim of the present paper is to assess the impact of fake accounts on the characteristics of local friendship networks between users of VKontakte website in Izhevsk (Russia). The authors highlight key characteristics recognizing a fake account and present experience of the design of classifier (based on random forest algorithm) to determine the authenticity of an account. Comparison of the VKontakte network topology before and after removing the fake accounts from it shows what specific network metrics are affected by the presence of fake profiles. It was found that as the fakes are being excluded the less integrated members lose contact with most part of the network while the number of its components increases. “Fakes” serve as strong link concentrators distributed throughout the network and these fakes overestimate observed levels of assortativity and transitivity

The paradigm-shift of social spambots: Evidence, theories, and tools for the arms race

Recent studies in social media spam and automation provide anecdotal argumentation of the rise of a new generation of spambots, so-called social spambots. Here, for the first time, we extensively study this novel phenomenon on Twitter and we provide quantitative evidence that a paradigm-shift exists in spambot design. First, we measure current Twitter's capabilities of detecting the new social spambots. Later, we assess the human performance in discriminating between genuine accounts, social spambots, and traditional spambots. Then, we benchmark several state-of-the-art techniques proposed by the academic literature. Results show that neither Twitter, nor humans, nor cutting-edge applications are currently capable of accurately detecting the new social spambots. Our results call for new approaches capable of turning the tide in the fight against this raising phenomenon. We conclude by reviewing the latest literature on spambots detection and we highlight an emerging common research trend based on the analysis of collective behaviors. Insights derived from both our extensive experimental campaign and survey shed light on the most promising directions of research and lay the foundations for the arms race against the novel social spambots. Finally, to foster research on this novel phenomenon, we make publicly available to the scientific community all the datasets used in this study.Comment: To appear in Proc. 26th WWW, 2017, Companion Volume (Web Science Track, Perth, Australia, 3-7 April, 2017