Age Detection in Chat

This paper presents the results of using statistical analysis and automatic text categorization to identify an author's age group based on the author's online chat posts. A naive Bayesian classifier and support vector machine (SVM) model were used. The SVM model experiments generated an f-...

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Bibliographische Detailangaben
Hauptverfasser:	Tam, J., Martell, C.H.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	age classification Bayesian methods Computer science Internet Law enforcement Naïve Bayesian Classifier Niobium compounds online chat Statistical analysis stop words Support Vector Machine Support vector machine classification Support vector machines Testing Text categorization
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Beschreibung
Zusammenfassung:	This paper presents the results of using statistical analysis and automatic text categorization to identify an author's age group based on the author's online chat posts. A naive Bayesian classifier and support vector machine (SVM) model were used. The SVM model experiments generated an f-score measurement of 0.996 on test data distinguishing teens from adults. We also introduce an alternative method for generating ldquostop wordsrdquo that chooses n-grams based on their relative distribution across the classes.
DOI:	10.1109/ICSC.2009.37