Classification of YouTube Data based on Sentiment Analysis

Nowadays, Big data and Data mining have attracted a great deal of attention in the information industry, due to the wide availability of huge amounts of data and the urgent need for turning such data into useful knowledge through predictive models.Corporate companies are using social media for improving their businesses, the data mining and analysis are very important in these days. Thus, Interaction and review are established with the customers and the concept, characteristics & need for Big Data & different offerings available in the market to explore unstructured large data. The paper deals with analysis of YouTube Data. The analysis is done using users Sentiments features such as Views, Comments, Likes, and Dislikes. We used the Linear Regression classification approach to classify the YouTube Data. The experimental results are given accurate results which illustrated that it is influential practice and a key enabler for the social business. The insights gained from the user generated online contents and collaboration with customers is critical for success in the age of social media.