Detecting spam in a Twitter network

Sarita Yardi, Daniel Romero, Grant Schoenebeck, danah boyd

Abstract


Spam becomes a problem as soon as an online communication medium becomes popular. Twitter’s behavioral and structural properties make it a fertile breeding ground for spammers to proliferate. In this article we examine spam around a one-time Twitter meme—“robotpickuplines”. We show the existence of structural network differences between spam accounts and legitimate users. We conclude by highlighting challenges in disambiguating spammers from legitimate users.

Keywords


social network analysis; microblogging; spam

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DOI: http://dx.doi.org/10.5210/fm.v15i1.2793



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