Corpus ID: 18394158

Fast Spammer Detection Using Structural Rank

@article{Kim2014FastSD,
  title={Fast Spammer Detection Using Structural Rank},
  author={Seungyeon Kim and Haesun Park and G. Lebanon},
  journal={ArXiv},
  year={2014},
  volume={abs/1407.7072}
}
Comments for a product or a news article are rapidly growing and became a medium of measuring quality products or services. Consequently, spammers have been emerged in this area to bias them toward their favor. In this paper, we propose an efficient spammer detection method using structural rank of author specific term-document matrices. The use of structural rank was found effective and far faster than similar methods. 
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