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Uncovering Structure-Rating Associations in Animated Film Character Networks.

Jue Zeng1, Yiwen Tang1, Xueming Liu1

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Higher-rated animated films feature more complex character networks with varied centrality and diverse relationships. This suggests that intricate, loosely connected character structures enhance audience engagement and narrative depth.

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Area of Science:

  • Computational social science
  • Network science
  • Film studies

Background:

  • Audience perception of animated films is influenced by narrative structure.
  • Quantitative analysis of character interaction networks and their impact on film ratings is limited.

Purpose of the Study:

  • To quantitatively investigate how character interaction network topology influences animated film ratings.
  • To apply complex network theory to analyze narrative structures in animated films.

Main Methods:

  • Analyzed 82 animated films using complex network theory.
  • Extracted character networks and examined topological features like centrality, density, and path length.
  • Assessed semantic diversity of relationships within networks.

Main Results:

  • Higher-rated films exhibit greater centrality heterogeneity and richer semantic diversity.
  • Films with higher ratings show lower network density and efficiency, with longer average shortest path lengths.
  • Structural patterns indicate loosely connected, hierarchical networks correlate with positive reception.

Conclusions:

  • Complex, hierarchical character networks enhance narrative complexity and audience engagement in animated films.
  • The study provides a data-driven framework for narrative design and analysis across various media.
  • Findings offer insights into the structural elements that contribute to successful storytelling.