Source-linked AI summary
Characterizing and modeling the dynamics of online popularity
Jacob Ratkiewicz, Filippo Menczer, Santo Fortunato, Alessandro Flammini, Alessandro Vespignani
TL;DR
The paper asks how online popularity changes over time, addressing limited dynamic validation of rich-get-richer explanations. It analyzes temporal popularity data from Wikipedia and the Chilean Web, then proposes a rank-shift model combining popularity-based growth with random exogenous shifts. Online popularity exhibits bursty, heavy-tailed magnitudes and inter-event times, while the model reproduces the main empirical distributions.
Problem
Temporal validation of rich-get-richer explanations for online popularity has been limited, despite popularity's effects on opinions, culture, policy, and profit.
Method
The paper analyzes temporal traffic and hyperlink data from Wikipedia and the Chilean Web and models them with preferential popularity growth plus stochastic rank shifts.
Results
Online popularity shows heavy-tailed burst magnitudes and inter-event times, and the rank-shift model reproduces the main empirical distributions.
Takeaways & Limitations
Popularity changes are captured more accurately by bursts involving random shifts in attention than by gradual proportional growth alone.
Takeaways & Limitations
The model is primarily descriptive and reproduces popularity-change distributions only at a coarse level.
Abstract
from arXiv · showhide
Online popularity has enormous impact on opinions, culture, policy, and profits. We provide a quantitative, large scale, temporal analysis of the dynamics of online content popularity in two massive model systems, the Wikipedia and an entire country's Web space. We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and inter-event time. We propose a minimal model combining the classic preferential popularity increase mechanism with the occurrence of random popularity shifts due to exogenous factors. The model recovers the critical features observed in the empirical analysis of the systems analyzed here, highlighting the key factors needed in the description of popularity dynamics.