Sentiment lexicons or BERT? A comparison of sentiment analysis approaches and their performance

Using a lexicon-based method, we have previously investigated emotions and sentiments in relation to the representation of landscape in Swiss literature, looking in particular at the differences between the rural and urban spaces portrayed in a corpus of Swiss novels written in German. The present paper takes a step forward, using manual annotation and advanced machine learning methods to train a fine-tuned model to recognise valence and arousal on a historical corpus. Our goals are higher levels of lexical coverage and validity when compared to our prior results obtained with sentiment lexicons.