Fame for sale: Efficient detection of fake Twitter followers

@article{Cresci2015FameFS,
  title={Fame for sale: Efficient detection of fake Twitter followers},
  author={Stefano Cresci and Roberto Di Pietro and Marinella Petrocchi and Angelo Spognardi and Maurizio Tesconi},
  journal={Decision Support Systems},
  year={2015},
  volume={80},
  pages={56-71}
}
Fake followers are those Twitter accounts specifically created to inflate the number of followers of a target account. Fake followers are dangerous for the social platform and beyond, since they may alter concepts like popularity and influence in the Twittersphere—hence impacting on economy, politics, and society. In this paper, we contribute along different dimensions. First, we review some of the most relevant existing features and rules (proposed by Academia and Media) for anomalous Twitter… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 44 references

Mathematical statistics and data analysis

  • J. Rice
  • Cengage Learning
  • 2006
Highly Influential
12 Excerpts

digitalevaluations), Analysis of Twitter followers of the US Presidential Election candidates

  • M. Camisani-Calzolari
  • Barack Obama and Mitt Romney (August
  • 2012
Highly Influential
10 Excerpts

The elements of statistical learning

  • J. Friedman, T. Hastie, R. Tibshirani
  • Vol. 1, Springer Series in Statistics
  • 2001
Highly Influential
3 Excerpts

A near real - time detection system for suspicious URLs in Twitter stream

  • D. Palsetia, A. N. Choudhary, J. Kim
  • IEEE Trans . Dependable Secur . Comput .
  • 2014

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