Emotion Dynamics in Movie Dialogues

TL;DR

This paper introduces a novel framework for tracking emotion dynamics in movie dialogues, revealing patterns in character emotional arcs and offering tools for broader behavioral and social science applications.

Contribution

It presents a new set of utterance emotion dynamics metrics inspired by psychology to analyze emotional arcs in narratives.

Findings

Characters tend to use more negative words over time.

Emotional discordance among characters increases until 90% of the story.

UED metrics can be applied in social sciences and public health.

Abstract

Emotion dynamics is a framework for measuring how an individual's emotions change over time. It is a powerful tool for understanding how we behave and interact with the world. In this paper, we introduce a framework to track emotion dynamics through one's utterances. Specifically we introduce a number of utterance emotion dynamics (UED) metrics inspired by work in Psychology. We use this approach to trace emotional arcs of movie characters. We analyze thousands of such character arcs to test hypotheses that inform our broader understanding of stories. Notably, we show that there is a tendency for characters to use increasingly more negative words and become increasingly emotionally discordant with each other until about 90 percent of the narrative length. UED also has applications in behavior studies, social sciences, and public health.