Are Proverbs the New Pythian Oracles? Exploring Sentiment in Greek Sayings
This work addresses sentiment mapping in Greek proverbs for linguistic and cultural researchers, but it is incremental as it applies existing NLP methods to a new dataset.
The study tackled sentiment analysis of Greek proverbs using LLMs, finding that LLMs can accurately classify sentiment in this non-conventional task and that negative sentiment is more prevalent in most areas of Greece.
Proverbs are among the most fascinating linguistic phenomena that transcend cultural and linguistic boundaries. Yet, much of the global landscape of proverbs remains underexplored, as many cultures preserve their traditional wisdom within their own communities due to the oral tradition of the phenomenon. Taking advantage of the current advances in Natural Language Processing (NLP), we focus on Greek proverbs, analyzing their sentiment. Departing from an annotated dataset of Greek proverbs, we expand it to include local dialects, effectively mapping the annotated sentiment. We present (1) a way to exploit LLMs in order to perform sentiment classification of proverbs, (2) a map of Greece that provides an overview of the distribution of sentiment, (3) a combinatory analysis in terms of the geographic position, dialect, and topic of proverbs. Our findings show that LLMs can provide us with an accurate enough picture of the sentiment of proverbs, especially when approached as a non-conventional sentiment polarity task. Moreover, in most areas of Greece negative sentiment is more prevalent.