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Characterizing and modeling the dynamics of activity and popularity
Peng Zhang1, Menghui Li2, Liang Gao3
1School of Science, Beijing University of Posts and Telecommunications, Beijing, P. R. China.
Plos One
|March 4, 2014
Summary
Social media networks show active users create more links to items. Inactive users trace popular items more intensely than active users, revealing network dynamics.
Area of Science:
- Social Network Analysis
- Information Science
- Web Science
Background:
- Social media platforms function as two-layer networks connecting users and items.
- Understanding user activity and item popularity dynamics is crucial in Web 2.0 environments.
- Existing research highlights the importance of cross-links in social media network evolution.
Purpose of the Study:
- To analyze the growth of user activity and item popularity in empirical social media networks.
- To investigate the relationship between user activity levels and item popularity tracing.
- To propose and validate a model for social media network evolution based on observed dynamics.
Main Methods:
- Empirical analysis of user activity and item popularity in four large-scale social media datasets (Amazon, Flickr, Delicious, Wikipedia).
- Measurement of user activity and item popularity by the number of associated cross-links.
- Development and numerical experimentation of an evolving network model driven by two-step random walks.
Main Results:
- Cross-links are predominantly created by active users and acquired by popular items.
- Users, in general, tend to engage with popular items.
- Inactive users exhibit a stronger tendency to trace popular items compared to active users.
Conclusions:
- User activity and item popularity in social media networks are interconnected and influenced by user engagement levels.
- The proposed two-step random walk model can qualitatively replicate observed network dynamics.
- Findings offer insights into the micro-dynamics governing activity and popularity in social media ecosystems.
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