The exponential growth of social media has fostered the spread of both negativity (hate speech) and supportive content, with the latter often categorized as hope speech—text promoting peace and a hopeful outlook. Recently, a few research works have been conducted on automatic detection of hope speech in different languages, including English, Tamil, Malayalam, Spanish and Kannada. However, to the best of our knowledge, there is no research on hope speech in Bengali language text. Despite Bengali’s significant presence on social media, hope speech detection in this language remains unexplored. Therefore, it is important to develop appropriate computational methods for the automatic detection of hope and non-hope speech in Bengali text. One possible reason for the lack of hope speech research in Bengali may be the unavailability of a suitable dataset or corpus for this purpose. This study presents the first curated and annotated dataset for hope speech in Bengali, enabling effective detection and analysis. Several state-of-the-art computational models are applied to the created dataset and the results obtained confirm the suitability of the dataset for hope speech research. Overall, this research provides a foundational resource for Bengali hope speech detection, contributing to multilingual social media analysis.