Sentiment analysis of malayalam tweets using machine learning techniques
S Soumya, Pramod K.V.
Abstract
Sentiment Analysis of Malayalam Tweets using Machine Learning techniques is done in this paper. The tweets are classified into positive and negative using different machine learning techniques such as Naive Bayes (NB), Support Vector Machine (SVM) and Random Forest (RF). The different features like Bag of Words (BOW), Term Frequency vs. Inverse Document Frequency (TF − IDF), Unigram with Sentiwordnet, and Unigram with Sentiwordnet including negation words are considered for feature vector formation of input dataset. The Random Forest classifier shows higher accuracy while considering Unigram with Sentiwordnet including negation words as a feature.
Topics & Concepts
Artificial intelligenceNaive Bayes classifiertf–idfSupport vector machineMalayalamComputer scienceRandom forestSentiment analysisNatural language processingMachine learningNegationClassifier (UML)Feature (linguistics)BigramTerm (time)Pattern recognition (psychology)TrigramLinguisticsPhilosophyProgramming languagePhysicsQuantum mechanicsSentiment Analysis and Opinion MiningAdvanced Text Analysis TechniquesText and Document Classification Technologies