Quora Question Sincerity Detection Using BERT-Based Framework

In the dynamic landscape of online knowledge exchange, platforms such as Quora have become vital arenas for diverse discussions and information dissemination. However, distinguishing sincere from insincere questions poses a challenge, impacting user experience and content credibility. The research seeks to utilize BERT-based frameworks to classify Quora questions, with a specific focus on discerning between sincere and insincere inquiries. The study underscores the significance of automated insincere content identification in fostering a trustworthy and constructive online environment on Quora, thereby contributing to the improvement of online interaction quality. The research delves into a comprehensive methodology, including data preprocessing, model training, fine-tuning, and performance evaluation. Extensive experimentation demonstrates that the proposed BERT-based approach achieves an impressive F1-score of 96.1%, outperforming existing methods. The contribution of the study lies in its potential to enhance online interactions by automating the identification of insincere content, fostering a conducive environment for meaningful conversations.