Episode
Sriniwas Pandey, Binghamton University - Platform Recommendations and Diverse Opinions on Social Media
- Podcast
- The Academic Minute
- Published
- May 28, 2026
- Duration seconds
- 150
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Summary
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…