Learning Similarity between Movie Characters and Its Potential Implications on Understanding Human Experiences

TL;DR

This paper introduces a novel approach to measure theme-level similarities between movie characters, leveraging community-curated themes to enhance understanding of human experiences and demonstrate potential applications in analyzing Reddit posts.

Contribution

It presents a new task and a two-step method for capturing thematic similarities, achieving significant improvements over existing paragraph-embedding techniques.

Findings

9-27% improvement over recent methods

Thematic information can help understand human experiences

Potential application in analyzing Reddit posts

Abstract

While many different aspects of human experiences have been studied by the NLP community, none has captured its full richness. We propose a new task to capture this richness based on an unlikely setting: movie characters. We sought to capture theme-level similarities between movie characters that were community-curated into 20,000 themes. By introducing a two-step approach that balances performance and efficiency, we managed to achieve 9-27\% improvement over recent paragraph-embedding based methods. Finally, we demonstrate how the thematic information learnt from movie characters can potentially be used to understand themes in the experience of people, as indicated on Reddit posts.