Detecting spam in a Twitter network
Keywords: social network analysis, microblogging, spam
AbstractSpam 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.
How to Cite
Yardi, S., Romero, D., Schoenebeck, G., & boyd, danah. (2009). Detecting spam in a Twitter network. First Monday, 15(1). https://doi.org/10.5210/fm.v15i1.2793
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