Sentiment Analysis of Public Opinion Towards Reverse Diabetic Videos

The amount of textual data has increased significantly over time, creating the potential for machine learning and natural language processing research. Nowadays, sentiment analysis of YouTube comments is a fascinating topic. Due to the inconsistent and poor quality of the data, not much has been done to pre-process the numerous user comments. In this study, we use machine learning approaches to do sentiment analysis on YouTube comments relating to hot subjects. Although several techniques for sentiment analysis have been created recently for the health sector, the field of reverse diabetes has not yet been much investigated based on YouTube video comment analysis. To categorise the dataset, the machine learning techniques like Naive Bayes, support vector machine, logistic regression, and random forest were utilised.