BACKGROUND Because the quality of information on the Internet is of dubious worth, many patients seek out reliable expert sources. As per the American Medical Association (AMA) and the National Institutes of Health (NIH) recommendations, readability of patient education materials should not exceed a sixth-grade reading level. The average reading skill of U.S. adults is at the eighth-grade level...

Readability metric is considered to be one of the most important factors that may affect games business in terms of evaluating games’ quality in general and usability in particular. As games may go through many evolutions and developed by many developers, code readability can significantly impact the time and resources required to build, update or maintain such games. This paper introduces a ne...

In this paper we present computational models to compute readability of Indian language text documents. We first demonstrate the inadequacy and the consequent inapplicability of some of the popular readability metrics in English to Hindi and Bangla. Next, we present user experiments to identify important structural parameters of Bangla and Hindi that affect readability of texts in these two lan...

Text readability refers to the ability of the reader to understand and comprehend a given text. In this research, we present our approach to develop an automatic readability index for the Arabic language: Automatic Arabic Readability Index (AARI), using factor analysis. Our results are based on more than 1196 Arabic texts extracted from the Jordanian curriculum in the subjects of: Arabic langua...

Objective. Patients use several online resources to learn about vocal cord paralysis (VCP). The objective of this study was to assess the readability and understandability of online VCP patient education materials (PEMs), with readability assessments and the Patient Education Materials Evaluation Tool (PEMAT), respectively. The relationship between readability and understandability was then ana...

s Scott Crossley Crowdsourcing text complexity models The current study builds on work by De Clercq et al. (2014) and Crossley et al. (2017) by using crowdsourcing techniques to collect human ratings of text comprehension, processing, and familiarity across a large corpus comprising a diverse variety of topic domains (science, technology, and history). Pairwise comparisons among the ratings wer...

In this paper we investigate how readability varies between texts originally written in English and texts translated into English. For quantification, we analyze several factors that are relevant in assessing readability – shallow, lexical and morpho-syntactic features – and we employ the widely used Flesch-Kincaid formula to measure the variation of the readability level between original Engli...

We combine lexical, syntactic, and discourse features to produce a highly predictive model of human readers’ judgments of text readability. This is the first study to take into account such a variety of linguistic factors and the first to empirically demonstrate that discourse relations are strongly associated with the perceived quality of text. We show that various surface metrics generally ex...

All readability research is ultimately concerned with the research question whether it is possible for a prediction system to automatically determine the level of readability of an unseen text. A significant problem for such a system is that readability might depend in part on the reader. If different readers assess the readability of texts in fundamentally different ways, there is insufficient...