From deliberation to acclamation: how did Twitter’s algorithms foster polarized communities and undermine democracy in the 2020 US presidential election

This study explores the profound effects of information and communication technologies (ICT) on contemporary democracy. Focusing on the 2020 US presidential election, this research investigates how Twitter/X structures online communities with specific socialization patterns and ways to construct the truth. The rise of these platforms has sparked debate with split conclusions over whether they are enhancing or undermining democratic processes. Rather than keep digging within this unsolved discussion, this study moves the focus of inquiring toward how ICT affects the very existence of subjects in democracy. This means transitioning from defining ICT solely by its utility as a separate technology that affects behavior to seeing how subjects are entangled in the virtual world created by ICT. Methodologically, the users’ practices on the web are mapped using computational sciences metrics. This study employed Twitter’s Stream API to assemble a dataset encompassing tweets that featured keywords. The descriptive analytics are executed utilizing the Python programming language. In conducting sentiment analysis, this research employed the Twitter-roBERTa-base model. To develop a comprehensive analysis of large interaction datasets, we propose a novel methodology leveraging large language models to automate the classification process. The analysis reveals how algorithmically driven virtual interactions create a “mixed reality,” where virtual and real-world dynamics intersect, leading to increased polarization and the erosion of democratic deliberation. Trump’s defeat marked a collision between users who took to the streets under the banner of a conspiracy theory, which had gained traction as an alternative virtual truth through acclamation as practice, and citizens who use the practice of deliberation over empirical results of the electoral process. This study not only provides empirical evidence on the impact of ICT on democracy but also introduces innovative computational techniques for analyzing large-scale social media data.