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.
|Title of host publication||Naturally-Inspired Artificial Intelligence - Papers from the AAAI Fall Symposium, Technical Report|
|Editors||Jacob Beal, Paul Bello, Nick Cassimatis, Michael Coen, Patrick Winston|
|Place of Publication||Arlington, VA|
|Number of pages||6|
|Publication status||Published - Nov 2008|
|Event||Proceedings of the AAAI Fall Symposium on Naturally-Inspired Artificial Intelligence - Arlington, Virginia|
Duration: 5 Nov 2008 → 7 Nov 2008
|Conference||Proceedings of the AAAI Fall Symposium on Naturally-Inspired Artificial Intelligence|
|Period||5/11/08 → 7/11/08|
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.