# Analysis of Basic Emotions in Texts Based on BERT Vector Representation

arXiv: https://arxiv.org/abs/2101.11433 · HTML: https://mlsanity.com/paper/2101.11433/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 9 references that are in the map.
- First posted on arXiv 21 Jan 2021.

## Builds on (most cited first, 3 of 3)

- [GoEmotions: A Dataset of Fine-Grained Emotions](https://mlsanity.com/paper/2005.00547/) (2020)
- [A Sequence-to-Sequence Approach to Dialogue State Tracking](https://mlsanity.com/paper/2011.09553/) (2020)
- [A BERT-based Dual Embedding Model for Chinese Idiom Prediction](https://mlsanity.com/paper/2011.02378/) (2020)

## Abstract (arXiv)

In the following paper the authors present a GAN-type model and the most important stages of its development for the task of emotion recognition in text. In particular, we propose an approach for generating a synthetic dataset of all possible emotions combinations based on manually labelled incomplete data.