Cognitive Load Theory as a Predictor for Citation Count

Abstract: The purpose of this study is to examine if the cognitive load that is induced from different degrees of text complexity in scientific abstracts has an influence on how often the study will get cited. While the influence of cognitive load is well documented in research of activities such as attention allocation, decision making and reading comprehension, it is not known whether such effects can also be applied to more complex activities, such as whether a scientific paper will be influential (or not). In the present study, text induced cognitive load in scientific abstracts is captured by using the of Gunning Fog Index (GFI) and Dale-Chall Score (DCS) for text complexity, while also analyzing with the Type-Token Ratio (TTR). These three text analysis tools capture varying levels of text complexity from word length, sentence length, and lexical sophistication and diversity, which have been shown to impact cognitive load. Apart from examining this relationship per se, the present study also investigates if the three measures of text induced cognitive load varies between different academic fields. The study found TTR to be significantly correlated with the citation count in all three search results while DCS and GFI were not. A post hoc analysis revealed only the DCS as having a significant difference for each comparison within academic disciplines.