  In this project, we tackle emotion classification for the Greek language,
presenting and releasing a new dataset in Greek. We fine-tune and assess
Transformer-based masked language models that were pre-trained on monolingual
and multilingual resources, and 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: (a) locate the months with the
highest values from 1989 to present, (b) rank the Greek political parties based
on the presence of this emotion in their speeches, and (c) study the emotional
context shift of words used to stigmatise people.
