# CroSentiNews 2.0: A Sentence-Level News Sentiment Corpus

arXiv: https://arxiv.org/abs/2305.08187 · HTML: https://mlsanity.com/paper/2305.08187/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 35 references that are in the map.
- First posted on arXiv 14 May 2023.

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

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Don't Stop Pretraining: Adapt Language Models to Domains and Tasks](https://mlsanity.com/paper/2004.10964/) (2020)
- [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)
- [Multilingual Twitter Sentiment Classification: The Role of Human Annotators](https://mlsanity.com/paper/1602.07563/) (2016)
- [Sentiment Analysis in the News](https://mlsanity.com/paper/1309.6202/) (2013)
- [FinEst BERT and CroSloEngual BERT: less is more in multilingual models](https://mlsanity.com/paper/2006.07890/) (2020)
- [Multi-task Learning for Cross-Lingual Sentiment Analysis](https://mlsanity.com/paper/2212.07160/) (2022)

## Abstract (arXiv)

This article presents a sentence-level sentiment dataset for the Croatian news domain. In addition to the 3K annotated texts already present, our dataset contains 14.5K annotated sentence occurrences that have been tagged with 5 classes. We provide baseline scores in addition to the annotation process and inter-annotator agreement.