# UG18 at SemEval-2018 Task 1: Generating Additional Training Data for Predicting Emotion Intensity in Spanish

arXiv: https://arxiv.org/abs/1805.10824 · HTML: https://mlsanity.com/paper/1805.10824/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 May 2018.

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

- [Towards More Accurate Prediction of Human Empathy and Emotion in Text and Multi-turn Conversations by Combining Advanced NLP, Transformers-based Networks, and Linguistic Methodologies](https://mlsanity.com/paper/2407.18496/) (2024)

## Abstract (arXiv)

The present study describes our submission to SemEval 2018 Task 1: Affect in Tweets. Our Spanish-only approach aimed to demonstrate that it is beneficial to automatically generate additional training data by (i) translating training data from other languages and (ii) applying a semi-supervised learning method. We find strong support for both approaches, with those models outperforming our regular models in all subtasks. However, creating a stepwise ensemble of different models as opposed to simply averaging did not result in an increase in performance. We placed second (EI-Reg), second (EI-Oc), fourth (V-Reg) and fifth (V-Oc) in the four Spanish subtasks we participated in.