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D'Mello, Sidney K.; Southwell, Rosy; Gregg, Julie – Discourse Processes: A Multidisciplinary Journal, 2020
We propose that machine-learned computational models (MLCMs), in which the model parameters and perhaps even structure are learned from data, can complement extant approaches to the study of text and discourse. Such models are particularly useful when theoretical understanding is insufficient, when the data are rife with nonlinearities and…
Descriptors: Discourse Analysis, Computer Software, Intervention, Computational Linguistics