Sweet Tweets Are Made of This: Extracting Anonymous Relation of Communities, Vocabularies, and Sentiment on Italian Social Media Interactions

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Abstract
In the social media age, platforms like X (formerly Twitter) are essential for spreading information and shaping public opinion. This initial study proposes a methodology to investigate interactions with Italian opinion leaders, forming clusters of leaders based on user engagement patterns while preserving user anonymity by analyzing the vocabulary eccentricity and sentiment analysis. Our findings reveal that positive sentiment is linked to a more eccentric vocabulary, particularly within specific clusters, indicating that sentiment is deeply linked to the community's shared language. Despite the prevalence of negative sentiment, most clusters feature a minority of leaders with eccentric, positive language. These consistent patterns over time suggest a potential universal behaviour for further study.

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