Patterns and Dynamics of Netflix TV Show Popularity

The rise of platforms like Netflix has expanded the possibility for audiences worldwide to watch the same content simultaneously, motivating research on cross-country media consumption. We investigate the global dynamics of media consumption by analyzing daily top-ranked Netflix TV shows across 71 countries over a span of 822 days. Using an information-theoretic framework, we measure diversity, similarity, and directional relationships in consumption trends using Shannon entropy, mutual information, and Kullback-Leibler (KL) divergence. According to Shannon entropy analysis, North America and Europe have highly dynamic viewing preferences, whereas East and Southeast Asia (ESA) display more persistent trends, with the same shows often dominating for long periods. Mutual information identifies clear regional clusters of synchronized consumption, with particularly strong alignment among ESA countries. To analyze temporal patterns, we introduce a KL-based asymmetry measure that captures directional patterns between countries, applicable to both inter- and intra-regional pairs. This analysis reveals distinct pathways of content spread. We find inter-regional patterns from ESA and South America toward North America and Europe, and intra-regional signals from Korea and Thailand to other ESA countries. We also observe that ESA trends reaching other regions often originate from Singapore. These findings offer insight into the temporal structure of global content spread and highlight the coexistence of global synchronization and regional independence in streaming media preferences.

💡 Research Summary

The paper investigates global patterns and directional flows of Netflix TV‑show popularity by applying information‑theoretic measures to a large‑scale dataset. The authors collected daily top‑ranked (rank 1) Netflix TV‑show data for 71 countries over 822 days (July 2020 – September 2022) via FlixPatrol, yielding 561 distinct shows. For each country k they define a discrete random variable X_k whose outcomes are the show indices, and estimate the empirical probability distribution P_k from the frequency of each show occupying the top spot.

First, Shannon entropy H(X_k)=−∑_s p(k,s)log₂p(k,s) quantifies the diversity of top‑ranked shows within a country. The results show a clear regional split: North America and Europe (the NAPE group) have high entropy (≥ 5.8), indicating rapidly changing preferences, whereas East and Southeast Asia (ESA) and Central‑South America (CSA) display lower entropy (≤ 5.5), reflecting a few long‑running dominant shows.

Second, mutual information I(X_k1,X_k2) measures similarity between two countries’ top‑show distributions. A symmetric matrix visualisation reveals two dense blocks: one encompassing NAPE and neighboring CSA/AME countries, and another confined to ESA nations. ESA countries exhibit strong internal mutual information but weak connections to other regions, suggesting a cohesive yet regionally isolated viewing pattern. Conversely, many NAPE and some Middle‑Eastern countries align closely with global trends.

Third, to capture temporal directionality the authors introduce a KL‑divergence‑based asymmetry measure: D_KL(P_i‖P_j)=∑_s p(i,s)log