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Dynamics of temporal influence in polarised networks
Caroline B Pena1, David J P O'Sullivan1, Pádraig MacCarron1
1Mathematics Applications Consortium for Science and Industry (MACSI), Department of Mathematics and Statistics, University of Limerick, Limerick, Ireland.
Plos One
|December 9, 2025
Summary
Identifying influential users in fragmented social networks is challenging due to community structures. This study analyzes temporal influence dynamics, finding modified temporal models best capture evolving user impact.
Area of Science:
- Social Network Analysis
- Information Diffusion Dynamics
- Computational Social Science
Background:
- Identifying influential users is crucial for marketing and understanding information spread.
- Polarized social networks exhibit fragmented structures, leading to information silos.
- User influence and its ranking can dynamically change over time.
Purpose of the Study:
- To investigate the temporal dynamics of user influence in fragmented social networks.
- To compare the stability of influence rankings using temporal centrality measures.
- To extend centrality measures to incorporate community structures and network evolution.
Main Methods:
- Utilized temporal centrality measures adapted for community structures.
- Analyzed network evolution behaviors and their impact on influence.
- Employed a modified temporal independent cascade model and temporal degree centrality.
Main Results:
- Successfully aggregated nodes into distinct influence bands.
- Demonstrated effective aggregation of centrality scores to analyze community influence over time.
- Identified specific models that reliably isolate nodes into their respective influence bands.
Conclusions:
- Temporal centrality measures, adapted for community structures, are effective for analyzing influence in fragmented networks.
- Modified temporal independent cascade model and temporal degree centrality show superior performance in dynamic influence analysis.
- Understanding temporal influence dynamics is key to navigating polarized and evolving social networks.
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