What happens when platforms recommend opinions instead of users?
Sriniwas Pandey, lecturer at the School of Computing at Binghamton University, details this.
Faculty Bio:
Pandey is a lecturer in the School of Computing at Binghamton University. He received his PhD degree in system science from Binghamton University. He holds bachelor's and master's degrees in computer science engineering from UTU India and IIITDMJ India, respectively. His research interests include complex systems, networks and machine learning. His research aims to comprehend the intricacies of eccentric behavior within society, focusing on identifying the underlying factors contributing to such behaviors and its impact on network dynamics.
Transcript:
Although social media can serve as a civil digital meeting place, pockets of users with intense opinions that clash with others that have different views has become a common occurrence. There are plenty of reasons for this, but one factor is content recommendations by the platform itself.
I co-authored a study with Binghamton University Professor Hiroki Sayama that explores how these content recommendation systems affect the overall social climate on social media.
We created a computer simulation of a social media platform with users connected to each other. Each user had a default set of opinions. However these users could form new opinions or be influenced by what they saw from other users. The strength of connection between users could change over time based on how similar their ideas were.
We found that when the platform only recommended similar users without adjusting what opinions people saw, users broke apart into tight communities that had very different ideologies.
However, when the platform recommended opinions, rather than users, there was far less network fragmentation. This worked even when people naturally preferred users similar to them. This also led to more unusual or off-center opinions. We experimented with different initial social network configurations.
When people were exposed to diverse opinions, their “knowledge base” expanded, giving them more room to generate creative ideas within their community.
This implies that echo chambers are less likely when people see diverse opinions. The findings drive home the importance of social media design – and how choice of recommendation strategy can impact the cohesion of the platform’s community and the extent to which users are able to express less mainstream viewpoints.
