Development of Youtube Sentiment Analysis Application using K-Nearest Neighbors (Nokia Case Study)

Nokia is a company that uses Youtube as a platform to advertise and market its products until now. Nokia was a cellphone company that had fallen in 2013 due to the company's unwillingness to follow the android operating system trend at the time. Nokia continues to rise and launch new products that are increasingly sophisticated. In seeing and summarizing public opinion towards Nokia's products, this research will develop a website-based application namely Youtube Sentiment Analysis. Application is built using Python and JavaScript with the Flask framework. In building the sentiment analysis model, this reseach use K-Nearest Neighbors algorithm with value of k=5 and getting an accuracy value of 88.6%. Application that has been built can carry out processes ranging from collecting comments using Selenium, labeling comments automatically using VaderSentiment, preprocessing comments using NLTK, weighting words using TFIDF, classifying using K-Nearest Neighbors algorithm, evaluating algorithms using confusion matrix, to visualizing classification and evaluation results in the form of pie charts, bar charts and confusion matrix.