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The Power of Social Networks and Social Media’s Filter Bubble in Shaping National Identities: An Agent-Based Model, 2019-2022
Creator
Chueca Del Cerro, C, Durham University
Study number / PID
856587 (UKDA)
10.5255/UKDA-SN-856587 (DOI)
Data access
Open
Series
Not available
Abstract
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...
Terminology used is generally based on DDI controlled vocabularies: Time Method, Analysis Unit, Sampling Procedure and Mode of Collection, available at CESSDA Vocabulary Service.
Methodology
Data collection period
01/09/2019 - 30/11/2022
Country
Not Applicable
Time dimension
Not available
Analysis unit
Individual
Event/process
Time unit
Universe
Not available
Sampling procedure
Not available
Kind of data
Numeric
Data collection mode
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.
Funding information
Grant number
2238184
Access
Publisher
UK Data Service
Publication year
2023
Terms of data access
The Data Collection is available to any user without the requirement for registration for download/access.