These are the modeling outputs from the ABM simulations included on the paper by the same title as this data collection that was awarded best PhD paper award at the Social Simulation conference September 4-8 2022 in Milan. The model developed in this paper explained the national identity dynamics in a context where social networks and social media platforms were explicitly modelled. This allowed to test the effects and resulting changes in national identities depending on the social networks and social media filter bubble conditions. Additionally, an empirically-informed version of the model was created with political attitudes survey data from the Catalan Centre of Opinion Studies 2011 to contextualise the model in Catalonia where there's an ongoing secessionist movement. This increases the validity of the model as it represents a population such as the Catalan one.Much of the recent debate in political sciences has been regarding the role social media's filtering algorithms play in the emergence of polarisation as well as the impact of the so-called echo chambers in this process. Social simulation scholars have provided valuable insights into the subject through opinion dynamics models and agent-based modelling approaches. While these models continue to be relevant, national identity polarisation remains an unsolved puzzle, especially in the current media environment of social media platforms. This article proposes a social simulation approach to the topic of opinion dynamics from a political communication perspective to understand how social network configurations and the media environment contribute to the emergence of national identity polarisation. We built an agent-based simulation model of national identity dynamics with a multilayer multiplex network of interacting agents in a hybrid media environment of both, traditional media and social media platforms. We use the Catalan secessionist movement to ground and contextualise our model. Using this simulation approach allows to disentangle the mechanisms through which social media filter bubbles and individual social networks may contribute to the emergence of national identity polarisation. We found that the initial social network setup conditions had a large impact on the emergence of national identity polarisation amongst agents. In particular, homophily-based social networks produced greater national identity polarisation compared to random networks, especially in the presence of social media filtering algorithms, selectively exposing agents to national identity-supportive information. Our results emphasise the importance of selective exposure by social media filtering algorithms and one's social networks for the polarisation of national identity. Therefore providing further evidence of the negative effects of social media platforms for polarisation and social cohesion, generally.

The data was produced by NetLogo Behaviour Space, imported into RStudio for data cleaning, preparation and analyses. An agent-based model in NetLogo produced these data.