Smokey: automatic recognition of hostile messages

  • Authors:
  • Ellen Spertus

  • Affiliations:
  • Microsoft Research, Massachusetts Institute of Technology, and University of Washington, Seattle, WA

  • Venue:
  • AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
  • Year:
  • 1997

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Abstract

Abusive messages (flames) can be both a source of frustration and a waste of time for Internet users. This paper . describes some approaches to flame recognition, mcluding a prototype system, Smokey. Smokey builds a 47-element feature vector based on the syntax and semantics of each sentence, combining the vectors for the sentences within each message. A training set of 720 messages was used by Quinlan's C4.5 decision-tree generator to determine feature-based rules that were able to correctly categorize 64% of the flames and 98% of the nonflames in a separate test set of 460 messages. Additional techniques for greater accuracy and user customization are also discussed.