Smokey: Automatic Recognition of Hostile Messages

Smokey: Automatic Recognition of Hostile Messages (1997)

by Ellen Spertus

Venue:	In Proc. IAAI
Citations:	48 - 0 self

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Datum	Value	Source
TITLE	Smokey: Automatic Recognition of Hostile Messages	INFERENCE
AUTHOR NAME	Ellen Spertus	SVM HeaderParse 0.1
AUTHOR AFFIL	Microsoft Research, MIT AI Lab, and University of Washington; Dept. of Computer Science and Engineering	SVM HeaderParse 0.2
AUTHOR ADDR	Box 352350; Seattle, WA 98195	SVM HeaderParse 0.1
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, including 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 featurebased rules that were able to correctly categorize 64% of the flames and 98% of the non-flames in a separate test set of 460 messages. Additional techniques for greater accuracy and user customization are also discussed. Introduction Flames are one of the current hazards of on-line communication. While some people enjoy exchanging flames, most users consider these abusive and insulting messages to be a nuisance or even upsetting. I describe Smokey, a prototype system to automatically recognize email flames. Smokey combines natural-langu...	user correction - Legacy Corrections
YEAR	1997	INFERENCE
VENUE	In Proc. IAAI	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	1058--1065	INFERENCE
CITATIONS	21 found	ParsCit 1.0