Readability and Comprehension of Digital Texts by Political Figures

Abstract

Previous research in the media field primarily focuses on analysing political communication within the context of social media, with limited attention given to the complexity of the political texts themselves. Therefore, this small-scale study aims to investigate the readability and comprehension of digital texts published by selected political figures on Facebook. Posts from political figures are selected based on specific criteria. Readability is calculated for 200 randomly selected posts. To determine the readability level of digital texts, we adapt a modified version of the readability formula, the FOG Index, along with Mistrík’s readability measure (R score). Additionally, respondents’ comprehension of 10 selected texts is evaluated through a Multiple-Choice Task Test. We employ a careful word deletion strategy when creating the tests, ensuring similar levels of context support across texts. A pilot test helps refine problematic distractors and ensure appropriate item difficulty using the Facility Value indicator. Due to the non-normal distribution of the collected data, this study employs nonparametric statistical methods in its analysis. This study finds significant differences in comprehension between texts from selected political figures. Education level is also found to be associated with comprehension (p = .023). Comprehension correlates with readability (R score: r(8) = 0.77, p = .009; FOG: r(8) = -0.9, p < .001). The modified FOG Index and R score are also correlated (r(8) = -0.67, p = .033), suggesting their interchangeability in similar Slovak studies.