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Abstract:

© 2010 Walter de Gruyter GmbH & Co. KG, Berlin/New York. Researchers in disciplines like lexical semantics and critical discourse analysis are in need of a quantitative method that allows them to model the distribution of a word automatically. We advocate the use of word space models, a family of approaches that were developed in the context of computational linguistics and cognitive science, which represent the meaning of a word in terms of its contexts in a large corpus. In a case study on the use of religious terms before and after the attacks of September 11, 2001, we show how these models can be employed to determine the semantic similarity and relatedness between two words, and the factors that influence them. One of the patterns we uncover is the increased association between Islam and terrorism in Dutch newspaper articles after 9/11, a trend that is far less outspoken for Christianity. We also apply these new quantitative instruments to explore the differences in word use between the five newspapers in our corpus, and find a striking distinction between popular and quality newspapers.