Modeling how social network algorithms can influence opinion polarization
arXiv:2102.00099 · doi:10.1016/j.ins.2021.12.069
Abstract
Among different aspects of social networks, dynamics have been proposed to simulate how opinions can be transmitted. In this study, we propose a model that simulates the communication in an online social network, in which the posts are created from external information. We considered the nodes and edges of a network as users and their friendship, respectively. A real number is associated with each user representing its opinion. The dynamics starts with a user that has contact with a random opinion, and, according to a given probability function, this individual can post this opinion. This step is henceforth called post transmission. In the next step, called post distribution, another probability function is employed to select the user's friends that could see the post. Post transmission and distribution represent the user and the social network algorithm, respectively. If an individual has contact with a post, its opinion can be attracted or repulsed. Furthermore, individuals that are repulsed can change their friendship through a rewiring. These steps are executed various times until the dynamics converge. Several impressive results were obtained, which include the formation of scenarios of polarization and consensus of opinions. In the case of echo chambers, the possibility of rewiring probability is found to be decisive. However, for particular network topologies, with a well-defined community structure, this effect can also happen. All in all, the results indicate that the post distribution strategy is crucial to mitigate or promote polarization.
References in corpus (16)
- Statistical physics of social dynamics
- Continuous Opinion Dynamics under Bounded Confidence: A Survey
- Minority Opinion Spreading in Random Geometry
- Modeling echo chambers and polarization dynamics in social networks
- Is the Voter Model a model for voters?
- Recent advances in opinion propagation dynamics: A 2020 Survey
- Social Influence and Unfollowing Accelerate the Emergence of Echo Chambers
- Quantifying echo chamber effects in information spreading over political communication networks
- Selective Exposure shapes the Facebook News Diet
- No Echo in the Chambers of Political Interactions on Reddit
- Emergence of polarized ideological opinions in multidimensional topic spaces
- Echo Chambers on Social Media: A comparative analysis
- Positive algorithmic bias cannot stop fragmentation in homophilic networks
- Co-evolutionnary network approach to cultural dynamics controlled by intolerance
- Opinion Diversity and Social Bubbles in Adaptive Sznajd Networks
- Contrarian effects and echo chamber formation in opinion dynamics