Princeton University Users: If you would like to view a senior thesis while you are away from campus, you will need to connect to the campus network remotely via the Global Protect virtual private network (VPN). If you are not part of the University requesting a copy of a thesis, please note, all requests are handled manually by staff and will require additional time to process.
 

Publication:

Opinion Dynamics in Digital Networks: Integrating Bounded Confidence and Expressed Private Opinion Models

dc.contributor.advisorRebrova, Elizaveta
dc.contributor.authorRiendeau-Krause, Dominic
dc.date.accessioned2025-08-06T14:04:20Z
dc.date.available2025-08-06T14:04:20Z
dc.date.issued2025-04-10
dc.description.abstractThis paper examines how opinions form in social networks, particularly when individuals look to a centralized source for the majority opinion. Motivated by the increasingly connected and selective nature of digital information platforms, this study introduces a new extension to the bounded confidence model that distinguishes between the expressed and private opinions of individuals. The proposed Expressed Private Opinion-Bounded Confidence (EPO-BC) model integrates two existing models to support a more complete understanding of how opinion clusters form, polarization emerges, and pluralistic ignorance develops in networked environments. Key findings show the potential role of centralized broadcasting in the creation of perceived consensus that hides underlying opinion diversity. While primarily theoretical, this research helps to explain and understand how digital platforms impact opinion formation and offers insights into mechanisms that may mitigate unfavorable dynamics in these networks.
dc.identifier.urihttps://theses-dissertations.princeton.edu/handle/88435/dsp01q237hw398
dc.language.isoen_US
dc.titleOpinion Dynamics in Digital Networks: Integrating Bounded Confidence and Expressed Private Opinion Models
dc.typePrinceton University Senior Theses
dspace.entity.typePublication
dspace.workflow.startDateTime2025-04-10T19:48:12.485Z
pu.contributor.authorid960543483
pu.date.classyear2025
pu.departmentOps Research & Financial Engr

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Thesis_Dominic.pdf
Size:
8.04 MB
Format:
Adobe Portable Document Format
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
100 B
Format:
Item-specific license agreed to upon submission
Description:
Download