Using temporal cohesion to predict temporal coherence in narrative and expository texts.

We investigated the linguistic features of temporal cohesion that distinguish variations in temporal coherence. In an analysis of 150 texts, experts rated temporal coherence on three continuous scale measures designed to capture unique representations of time. Coh-Metrix, a computational tool that assesses textual cohesion, correctly predicted the human ratings with five features of temporal cohesion. The correlations between predicted and actual scores were all statistically significant. In a complementary study, we explored the importance of temporal cohesion in characterizing genre. A discriminant function analysis, using Coh-Metrix temporal indices, successfully distinguished the genres of science, history, and narrative texts. The results suggested that history texts are more similar to narrative texts than to science texts in terms of temporal cohesion.