Content area
Text sentiment is a way of extracting data and transforming it into meaningful sentiment. In this research study, we tried to extract Urdu text data linked to medicine and convert it into a useful format that can be used to create an application. Electronic media quickly provides a large amount of information in any language, but it is unstructured and raw, making easily available data difficult to understand. Urdu is the most sought-after language in Asian countries, and the majority prefer this language. The sole distinction between the Urdu and Hindi languages is their writing script. However, the Roman scripts of both languages are comparable. In the Urdu dataset, pre-processing, feature engineering, and other approaches are utilized to extract clean data that can be easily trained using multiple machine learning models because the application that is going to be built requires only medical-related datasets retrieved from external sources, i.e., websites, newspapers, blogs, and other physical resources, the techniques used are appropriate.