# CHARET: Character-centered Approach to Emotion Tracking in Stories

arXiv: https://arxiv.org/abs/2102.07537 · HTML: https://mlsanity.com/paper/2102.07537/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 45 references that are in the map.
- First posted on arXiv 15 Feb 2021.

## Builds on (most cited first, 8 of 8)

- [COMET: Commonsense Transformers for Automatic Knowledge Graph Construction](https://mlsanity.com/paper/1906.05317/) (2019)
- [AllenNLP: A Deep Semantic Natural Language Processing Platform](https://mlsanity.com/paper/1803.07640/) (2018)
- [Modeling Naive Psychology of Characters in Simple Commonsense Stories](https://mlsanity.com/paper/1805.06533/) (2018)
- [Ranking and Selecting Multi-Hop Knowledge Paths to Better Predict Human Needs](https://mlsanity.com/paper/1904.00676/) (2019)
- [Extracting Action Sequences from Texts Based on Deep Reinforcement Learning](https://mlsanity.com/paper/1803.02632/) (2018)
- [Social Commonsense Reasoning with Multi-Head Knowledge Attention](https://mlsanity.com/paper/2010.05587/) (2020)
- [Modeling Label Semantics for Predicting Emotional Reactions](https://mlsanity.com/paper/2006.05489/) (2020)
- [Domain Authoring Assistant for Intelligent Virtual Agents](https://mlsanity.com/paper/1904.03266/) (2019)

## Abstract (arXiv)

Autonomous agents that can engage in social interactions witha human is the ultimate goal of a myriad of applications. A keychallenge in the design of these applications is to define the socialbehavior of the agent, which requires extensive content creation.In this research, we explore how we can leverage current state-of-the-art tools to make inferences about the emotional state ofa character in a story as events unfold, in a coherent way. Wepropose a character role-labelling approach to emotion tracking thataccounts for the semantics of emotions. We show that by identifyingactors and objects of events and considering the emotional stateof the characters, we can achieve better performance in this task,when compared to end-to-end approaches.