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In this project, we tackle emotion classification for the Greek language,presenting and releasing a new dataset in Greek. We fine-tune and assessTransformer-based masked language models that were pre-trained on monolingualand multilingual resources, and we present the results per emotion and byaggregating at the sentiment and subjectivity level. The potential of thepresented resources is investigated by detecting and studying the emotion of`disgust' in the Greek Parliament records. We: (a) locate the months with thehighest values from 1989 to present, (b) rank the Greek political parties basedon the presence of this emotion in their speeches, and (c) study the emotionalcontext shift of words used to stigmatise people.

Analysing the Greek Parliament Records with Emotion Classification