Textual coherence using Latent Semantic Analysis

Abstract

Latent Semantic Analysis is used as a technique for measuring the coherence of texts. By comparing the vectors for two adjoining segments of text in a high- dimensional semantic space, the method provides a characterization of the degree of semantic relatedness between the segments. We illustrate the approach for predicting coherence through re-analyzing sets of texts from two studies that manipulated the coherence of texts and assessed readers' comprehension. The results indicate that the method is able to predict the effect of text coherence on comprehension and is more effective than simple term-term overlap measures. In this manner, LSA can be applied as an automated method that produces coherence predictions similar to propositional modeling. We describe additional studies investigating the application of LSA to analyzing discourse structure and examine the potential of LSA as a psychological model of coherence effects in text comprehension.