Topic modeling is a data analysis technique that has become increasingly popular in recent years due to the growing availability of large datasets. It enables researchers to uncover underlying themes and topics within large and complex datasets by identifying patterns and relationships among data points. This article overviews the topic modeling process, including the algorithms used, tools, evaluation metrics, and applications across various fields. It also discusses potential areas for future research, such as integrating other machine learning techniques and incorporating temporal and contextual information. Overall, topic modeling represents a powerful tool for data analysis that has the potential to unlock new insights and understanding in a variety of domains
