This project finetunes and assesses Transformer-based masked language models that were pre-trained on monolingual and multilingual resources. We present the results per emotion and by aggregating at the sentiment and subjectivity level. The potential of the presented resources is investigated by detecting and studying the emotion of ‘disgust’ in the Greek Parliament records.
We:
- locate the months with the highest values from 1989 to present,
- rank the Greek political parties based on the pres- ence of this emotion in their speeches, and
- study the emotional context shift of words used to stigmatise people.
If you find this dataset useful, please cite us as:
@article{pavlopoulos2022analysing,
title={Analysing the Greek Parliament Records with Emotion Classification},
author={Pavlopoulos, John and Lislevand, Vanessa},
journal={arXiv preprint arXiv:2205.12012},
year={2022}
}