Structural complexity predicts consensus readability in online discussions

Abstract

The intricate relationship between structure and function spans various disciplines, from biology to management, offering insights into predicting interesting features of complex systems. This interplay is evident in online forums, where the organization of the threads interacts with the message’s meaning. Assessing readability in these discussions is vital for ensuring information comprehension among diverse audiences. This assessment is challenging due to the complexity of natural language compounded by the social and temporal dynamics within social networks. One practical approach involves aggregating multiple readability metrics as a consensus alignment. In this study, we explore whether the structural complexity of online discussions can predict consensus readability without delving into the semantics of the messages. We propose a consensus readability metric derived from well-known readability tests and a complexity metric applied to the tree structures of Reddit discussions. Our findings indicate that this proposed metric effectively predicts consensus readability based on the complexity of discourse structure.