What is it about?

Online social media platforms are nowadays spaces where political opinions are formed, reinforced, and confronted. These platforms are also environments where humans co-exist with algorithms recommending new connections between users. We show that preferentially establishing links between people sharing many friends — as often suggested by some link recommendation algorithms — potentiates opinion polarization by creating network topologies with isolated communities. This happens as isolated groups are more likely to sustain diverging opinions and lead individuals to be less exposed to a diverse pool of viewpoints. By contrast, preferentially linking nodes with few common connections has the potential to moderate opinions.

Featured Image

Why is it important?

The long-term effects of algorithmic recommendations, here concerning opinion formation, are often hard to anticipate. In this context, our study is relevant for three key reasons: first, it sheds light on the impacts of social-network algorithms in dynamics of polarization and consensus; second, it suggests that small modifications in how recommendations are made can have important impacts in forming polarized opinions; finally, and more broadly, it reveals that understanding the impacts of algorithms in our society requires framing their effects in the context of complex adaptive systems where individuals (co-)adapt to each other over time.


I hope this article makes readers question the potential impacts of social network algorithms in forming new connections between users and, in turn, affecting polarization dynamics. I would be thrilled if our study inspires new research or the design of practical interventions to curb polarization. Finally, for me it was an enriching experience to work on a topic lying at the interface of computer science, political science, and complex systems. Hopefully our work will invite future research in this area, inspiring new theoretical and empirical analysis that investigate how algorithms might provide link recommendations that are both useful for users and beneficial for society in the long-run.

Fernando P. Santos
Universiteit van Amsterdam

Read the Original

This page is a summary of: Link recommendation algorithms and dynamics of polarization in online social networks, Proceedings of the National Academy of Sciences, December 2021, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2102141118.
You can read the full text:



The following have contributed to this page