Textual Patterns and Virality in X: An Analysis of Engagement in Telenovela Posts

Abstract

X, previously known as Twitter, boasts 556 million active users and is widely used by businesses to engage with their audiences. In our study, we focused on TV Globo's telenovela "Terra e Paixão" broadcast in 2023, to analyze the impact of textual patterns on post virality using natural language processing techniques. Techniques like sentiment analysis, Part-Of-Speech Tagging, reinforcement scoring, TF-IDF, semantic similarity, and cosine similarity were utilized to identify attributes that contribute to a post's success, aiming to enhance marketing strategies. We employed language models like BERT, RoBERTa, and e5 in our analysis. Our findings indicate that while various metrics affect post engagement, the challenge remains complex. Textual characteristics, although essential, do not fully explain a publication's popularity, underscoring the need for a multifaceted approach to understanding social media dynamics.