Hope Speech

Hope speech, encompassing supportive and encouraging communication, is a burgeoning research area focusing on its automated detection and analysis within social media and other textual data. Current research employs various machine learning approaches, including lexicon-based sentiment analysis, traditional and deep learning classifiers, and transformer models, often leveraging contextual embeddings to improve accuracy. This work aims to develop efficient and reliable methods for identifying hope speech, contributing to a better understanding of its impact on mental well-being and potentially informing interventions to promote positive online interactions. The development of robust hope speech detection tools could have significant implications for mental health monitoring and the design of more supportive online communities.