A Dynamical Systems Approach to Bots and Online Political Communication

TL;DR

This paper uses dynamical systems theory and information-theoretic measures to analyze how political bots influence the complexity and uncertainty of online political discussions on Twitter.

Contribution

It introduces a novel application of dynamical systems and information theory to quantify the macro-level impact of political bots on online communication dynamics.

Findings

Bot activity increases complexity of communication dynamics.

Bot activity raises uncertainty in online political discussions.

The approach models human-bot interactions as a computational process.

Abstract

Bots have become increasingly prevalent in the digital sphere and have taken up a proactive role in shaping democratic processes. While previous studies have focused on their influence at the individual level, their potential macro-level impact on communication dynamics is still little understood. This study adopts an information theoretic approach from dynamical systems theory to examine the role of political bots shaping the dynamics of an online political discussion on Twitter. We quantify the components of this dynamic process in terms of its complexity, predictability, and the remaining uncertainty. Our findings suggest that bot activity is associated with increased complexity and uncertainty in the structural dynamics of online political communication. This work serves as a showcase for the use of information-theoretic measures from dynamical systems theory in modeling human-bot dynamics as a computational process that unfolds over time.