Twitter: Who gets caught? Observed trends in social micro-blogging spam

Abdullah Almaatouq, Ahmad Alabdulkareem, Mariam Nouh, Erez Shmueli, Mansour Alsaleh, Vivek K. Singh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Spam in Online Social Networks (OSNs) is a systemic problem that imposes a threat to these services in terms of undermining their value to advertisers and potential investors, as well as negatively affecting users' engagement. In this work, we present a unique analysis of spam accounts in OSNs viewed through the lens of their behavioral characteristics (i.e., profile properties and social interactions). Our analysis includes over 100 million tweets collected over the course of one month, generated by approximately 30 million distinct user accounts, of which over 7% are suspended or removed due to abusive behaviors and other violations. We show that there exist two behaviorally distinct categories of twitter spammers and that they employ different spamming strategies. The users in these two categories demonstrate different individual properties as well as social interaction patterns. As the Twitter spammers continuously keep creating newer accounts upon being caught, a behavioral understanding of their spamming behavior will be vital in the design of future social media defense mechanisms.

Original languageEnglish
Title of host publicationWebSci 2014 - Proceedings of the 2014 ACM Web Science Conference
Number of pages9
StatePublished - 2014
Externally publishedYes
Event6th ACM Web Science Conference, WebSci 2014 - Bloomington, IN, United States
Duration: 23 Jun 201426 Jun 2014

Publication series

NameWebSci 2014 - Proceedings of the 2014 ACM Web Science Conference


Conference6th ACM Web Science Conference, WebSci 2014
Country/TerritoryUnited States
CityBloomington, IN


  • Account abuse
  • Microblogging
  • Online social networks
  • Spam

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications


Dive into the research topics of 'Twitter: Who gets caught? Observed trends in social micro-blogging spam'. Together they form a unique fingerprint.

Cite this