Sentiment Analysis of Twitter Feeds Using Flask Environment: A Superior Application of Data Analysis

In this challenging world, social media plays a vital role as it is at the pinnacle of data sharing. The advancement in technology has made huge amount information available for analysis and on hotlist nowadays. Opinions people are expressed shared across various platforms like Twitter, Facebook, Instagram. Twitter prodigious platform containing an ample analyzing topmost priority. One most widely utilized approaches classifying individual’s emotions displayed subjective sentiment analysis. Sentiment done using algorithms machine learning Support Vector Machine, Naive Bayes, Long Short-Term Memory, Decision Tree Classifier, many more, but paper aims generalized way performing flask environment. Flask environment provides inbuilt functionalities to analyze sentiments text into three different categories: positive, negative, neutral. Also, makes API calls Developer account fetch data. After fetching data, results get webpage percentage neutral tweets phrase pie chart. It displays language same phrase. Furthermore, attention that reveals details tweets. Considering major industry runners sectors namely Enterprises, Sports Apparel Industry, Multimedia we have analyzed compared two Multinational companies from each sector.