We present a computational notion of Lexical Tightness that measures global cohesion of content words in a text. Lexical tightness represents the degree to which a text tends to use words that are highly inter-associated in the language. We demonstrate the utility of this measure for estimating text complexity as measured by US school grade level designations of texts. Lexical tightness strongl...

Engagement during reading can be measured by the amount of time readers invest in the reading process. It is hypothesized that disengagement is marked by a decrease in time investment as compared with the demands made on the reader by the text. In this study, self-paced reading times for screens of text were predicted by a text complexity score called formality; formality scores increase with c...

Engagement during reading can be measured by the amount of time readers invest in the reading process. It is hypothesized that disengagement is marked by a decrease in time investment as compared with the demands made on the reader by the text. In this study, self-paced reading times for screens of text were predicted by a text complexity score called formality; formality scores increase with c...

Collocational word similarity is considered a source of text cohesion that is hard to measure and quantify. The work presented here explores the use of information from a training corpus in measuring word similarity and evaluates the method in the text segmentation task. An implementation, the VecTile system, produces similarity curves over texts using pre-compiled vector representations of the...

Cultures differ on their expectations for the roles writers and readers take in relation to a text. According to John Hinds (1987), some cultures (like the US) favor “writer-responsible” writing, in which the writer has the primary responsibility for making sure that ideas are clearly communicated to the reader, while other cultures (like Japan) favor “reader-responsible” writing, in which the ...

We focused on the controversy whether high-performing readers consistently underestimate their comprehension or are prone to detrimental overestimations as much as less skilled readers are. Therefore, we conducted an experiment (N = 105 university students) to investigate judgment bias as a function of reading skill and text difficulty in terms of text cohesion. Results showed that the easy tex...

We present a graph-based model for representing the lexical cohesion of a discourse. In the graph structure, vertices correspond to the content words of a text and edges connecting pairs of words encode how closely the words are related semantically. We show that such a structure can be used to distinguish literal and non-literal usages of multi-word expressions.

We evaluated the effectiveness of new indices of text comprehension in measuring relative text difficulty. Specifically, we examined the efficacy of automated indices produced by the web-based computational tool Coh-Metrix. In an analysis of 60 instructional science texts, we divided texts into groups that were considered to be more or less difficult to comprehend. The defining criteria were ba...

This study aims at arousing college students’ metacognition in detecting lexical cohesion during online text construction as WordNet served as a lexical resource. A total of 83 students were requested to construct texts through sequences of actions identified as interaction chains in this study. Interaction chains are grouped and categorized as a meaningful entity in order to investigate the st...

This paper presents a novel unsupervised method for hierarchical topic segmentation. Lexical cohesion – the workhorse of unsupervised linear segmentation – is treated as a multi-scale phenomenon, and formalized in a Bayesian setting. Each word token is modeled as a draw from a pyramid of latent topic models, where the structure of the pyramid is constrained to induce a hierarchical segmentation...