Detecting spam in a Twitter network
Keywords:
social network analysis, microblogging, spam
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.
Published
2009-12-30
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
Section
Articles
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