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R: Mining Spatial, Text, Web, and Social Media Data by Richard Heimann, Nathan Danneman, Pradeepta Mishra, Bater Makhabel

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Case study 3 – IRT models for unsupervised sentiment scaling

The theoretical underpinnings of IRT models were set out in the previous chapter. Here, we briefly review them before demonstrating how to implement this class of models. However, readers should note that this class of model is cutting-edge, to the point of being considered experimental.

IRT models for text analysis start with the strong assumption that texts (or authors thereof) lie along a continuum, and that this continuum directly affects their word choices in a monotonic way such that if word use is likely at one end of the spectrum, it is unlikely at the other. These assumptions are somewhat restrictive; we can only scale texts that deal with moderately narrow topics and that are ...

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