PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Automatically Profiling the Author of an Anonymous Text
Shlomo Argamon, Moshe Koppel, James Pennebaker and Jonathan Schler
Communications of the ACM Volume 52, Number 2, pp. 119-123, 2009.

Abstract

Imagine that you have been given an important text of unknown authorship, and wish to know as much as possible about the unknown author (demographics, personality, cultural background, etc.), just by analyzing the given text. This authorship profiling problem is of growing importance in the current global information environment – applications abound in forensics, security, and commercial settings. For example, authorship profiling can help police identify characteristics of the perpetrator of a crime when there are too few (or too many) specific suspects to consider. On the other hand, large corporations may be interested in knowing what types of people like or dislike their products, based on analysis of blogs and online product reviews. The question we therefore ask is: How much can we discern about the author of a text simply by analyzing the text itself? It turns out that, with varying degrees of accuracy, we can say a great deal indeed.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Information Retrieval & Textual Information Access
ID Code:4688
Deposited By:Moshe Koppel
Deposited On:08 March 2010