Reading the Media’s Mind
‘There’s no art to find the mind’s construction in the face,’ wrote Shakespeare, but trying to infer what someone is really thinking is arguably the essence of interaction between cognitive agents. Turning this into a computational model is challenging, but one possible approach to infer mental models from linguistic expression is to look at patterns of lexical associations. Assuming that written language reflects conceptual associations in the writer’s mind, we have previously shown differences in the patterns of lexical association between creative and non-creative writing. In this paper, we apply the same approach to news reports from individual media sources over the same period, with the goal of looking for differential associative patterns. The underlying assumption is that the associative patterns of a media source will reflect its “mind” and “personality,” i.e., specific styles, preferences, or biases, just as they do for individuals.
KeywordsCognitive Graph theory Machine learning
This work was supported in part by National Science Foundation INSPIRE grant BCS-1247971 to Ali Minai.
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