A Narrative-Expectation-Based Approach to Temporal Update in Discourse Comprehension

Temporal-order iconicity bias in narrative event understanding and memory

Incongruence between the narrated (encoded) order and the actual chronological order of events is ubiquitous in various kinds of narratives and information modalities. The iconicity assumption in text comprehension proposes that readers will by default assume the chronological order to match the narrated order. However, it is not clear whether this iconicity assumption would directly bias inferred chronology of events and memory of their narrated order. In the current study, using non-linearly narrated video narratives as encoding materials, we dissociated the narrated order and the underlying chronological order of events. In Experiment 1, we found that participants' judgments of the chronological order of events were biased by the narrated order, but not vice versa. In Experiment 2, when the chronological positions of events were provided during encoding, participants' judgments of the chronological order were not biased by the narrated order, rather, their memory of the narrated order of events was biased by the chronological order. Interpreting the bias under a descriptive Bayesian framework, we offer a new perspective on the role of the iconicity assumption as prior belief, apart from prior knowledge about event sequences, in event understanding as well as memory.

Time and Causation in Discourse: Temporal Proximity, Implicit Causality, and Re-mention Biases

Using referential processing in discourse featuring implicit causality verbs as a test case, we demonstrate how a discourse's causal and temporal dimensions interact. We show that referential processing is affected by multiple discourse biases, and that these biases do not have uniform effects. In three discourse continuation experiments, we show that the bias to re-mention a particular referent in discourse involving implicit causality verbs is not only affected by the verb's implicit causality bias, but also by the discourse's temporal structure, which at times, can even override the implicit causality bias. Our results add to the growing number of studies that show how various discourse dimensions interact in discourse processing.