# EmoAtt at EmoInt-2017: Inner attention sentence embedding for Emotion Intensity

arXiv: https://arxiv.org/abs/1708.05521 · HTML: https://mlsanity.com/paper/1708.05521/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Aug 2017.

## Built on by (most cited first, 1 of 1)

- [Large Language Models on Fine-grained Emotion Detection Dataset with Data Augmentation and Transfer Learning](https://mlsanity.com/paper/2403.06108/) (2024)

## Abstract (arXiv)

In this paper we describe a deep learning system that has been designed and built for the WASSA 2017 Emotion Intensity Shared Task. We introduce a representation learning approach based on inner attention on top of an RNN. Results show that our model offers good capabilities and is able to successfully identify emotion-bearing words to predict intensity without leveraging on lexicons, obtaining the 13th place among 22 shared task competitors.