Twitter Sentiment Analysis Using Machine Learning Algorithms: A Case Study
Sheresh Zahoor, Rajesh Rohilla
Abstract
Sentiment analysis, also referred to as opinion mining or emotion extraction is the classification of emotions within a textual data. This technique has been widely used over the years in order to determine the sentiments, emotions within a particular textual data. Twitter is a social media platform that has been mostly used by people to express emotions for particular events. In this paper, we have collected tweets for a number of events, analyzed them using a number of Machine Learning algorithms like Naïve Bayes, SVM, Random Forest classifier and LSTM and compared the results.
Topics & Concepts
Sentiment analysisNaive Bayes classifierComputer scienceSupport vector machineSocial mediaArtificial intelligenceRandom forestMachine learningStatistical classificationClassifier (UML)Natural language processingAlgorithmWorld Wide WebSentiment Analysis and Opinion MiningSpam and Phishing DetectionText and Document Classification Technologies