Detecting the evolution of semantics and individual beliefs through statistical analysis of language use

A Bilovich, J J Bryson

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Individual differences in semantics and beliefs have up to now been identified primarily by questioning people. However, semantics and beliefs can also be observed in concrete, quantifiable contexts such as reaction-time experiments. Here we demonstrate an automatic mechanism which can replicate such semantics by observing regularities in language use through statistical text analysis. We postulate that human children, who are fantastic pattern recognizers, may also exploit this same information, thus our mechanism may be an essential module in a human-like cognitive system. In this article we first review the underlying theories and existing results, then present the tool itself. We validate the tool against existing semantic priming reaction-time results. Finally we use the tool to explore the evolution of beliefs extracted from three sources: the Bible, the works of Shakespeare and the contemporary British National Corpus.
Original languageEnglish
Title of host publicationNaturally-Inspired Artificial Intelligence - Papers from the AAAI Fall Symposium, Technical Report
EditorsJacob Beal, Paul Bello, Nick Cassimatis, Michael Coen, Patrick Winston
Place of PublicationArlington, VA
PublisherAAAI Press
Pages21-26
Number of pages6
ISBN (Print)9781577353980
Publication statusPublished - Nov 2008
EventProceedings of the AAAI Fall Symposium on Naturally-Inspired Artificial Intelligence - Arlington, Virginia
Duration: 5 Nov 20087 Nov 2008

Conference

ConferenceProceedings of the AAAI Fall Symposium on Naturally-Inspired Artificial Intelligence
CityArlington, Virginia
Period5/11/087/11/08

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    Bilovich, A., & Bryson, J. J. (2008). Detecting the evolution of semantics and individual beliefs through statistical analysis of language use. In J. Beal, P. Bello, N. Cassimatis, M. Coen, & P. Winston (Eds.), Naturally-Inspired Artificial Intelligence - Papers from the AAAI Fall Symposium, Technical Report (pp. 21-26). AAAI Press.