# A Spanish dataset for Targeted Sentiment Analysis of political headlines

arXiv: https://arxiv.org/abs/2208.13947 · HTML: https://mlsanity.com/paper/2208.13947/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 37 references that are in the map.
- First posted on arXiv 30 Aug 2022.

## Builds on (most cited first, 10 of 10)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding](https://mlsanity.com/paper/1804.07461/) (2018)
- [SemEval-2017 Task 4: Sentiment Analysis in Twitter](https://mlsanity.com/paper/1912.00741/) (2019)
- [Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence](https://mlsanity.com/paper/1903.09588/) (2019)
- [What the [MASK]? Making Sense of Language-Specific BERT Models](https://mlsanity.com/paper/2003.02912/) (2020)
- [MarIA: Spanish Language Models](https://mlsanity.com/paper/2107.07253/) (2021)
- [BERTIN: Efficient Pre-Training of a Spanish Language Model using Perplexity Sampling](https://mlsanity.com/paper/2207.06814/) (2022)
- [RoBERTuito: a pre-trained language model for social media text in Spanish](https://mlsanity.com/paper/2111.09453/) (2021)

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

- [LLMs for Targeted Sentiment in News Headlines: Exploring the Descriptive-Prescriptive Dilemma](https://mlsanity.com/paper/2403.00418/) (2024)

## Abstract (arXiv)

Subjective texts have been studied by several works as they can induce certain behaviours in their users. Most work focuses on user-generated texts in social networks, but some other texts also comprise opinions on certain topics and could influence judgement criteria during political decisions. In this work, we address the task of Targeted Sentiment Analysis for the domain of news headlines, published by the main outlets during the 2019 Argentinean Presidential Elections. For this purpose, we present a polarity dataset of 1,976 headlines mentioning candidates in the 2019 elections at the target level. Preliminary experiments with state-of-the-art classification algorithms based on pre-trained linguistic models suggest that target information is helpful for this task. We make our data and pre-trained models publicly available.