Temporal and Content Coupling Analysis of Social Media User Behavior

• URL: http://arxiv.org/abs/2604.27530v1
• Date: Thu, 30 Apr 2026 07:32:19 GMT
• Title: Temporal and Content Coupling Analysis of Social Media User Behavior
• Abstract summary: This study proposes a multi-scale temporal-content framework and validates it on two large real-world news datasets, MIND and Adressa.<n>Results reveal hierarchical temporal patterns.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: News consumption behavior is shaped by the coupling between temporal dynamics and content selection. This study proposes a multi-scale temporal-content framework and validates it on two large real-world news datasets, MIND and Adressa. Results reveal hierarchical temporal patterns. At the macroscale, Fourier modeling identifies clear circadian rhythms; at the mesoscale, session intervals follow a power-law distribution with $α\approx 1$; and at the microscale, within-session action counts and inter-action intervals follow exponential distributions with $λ\approx 0.3$ and $λ\approx 0.02$, respectively. Content analysis shows that clicks are mainly driven by historical interests, while this dependence weakens as content diversity increases. Temporal-content coupling further indicates that users' historical interests dominate active time periods in shaping behavior. Preference groups also differ: timeliness and entertainment-oriented users click more frequently and rely more on historical interests, whereas diversified users click less and are more sensitive to content diversity.

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