A Comparative Evaluation of Different Sentiment Analysis Algorithms for Social Media Text Analysis

the motive of this observe changed into to evaluate and examine the performance of different sentiment evaluation algorithms especially tailor-made to social media text evaluation. Four specific system learning algorithms were decided on for this look at: Naive Bayes, guide Vector Machines, Logistic Regression, and maximum Entropy. Several experiments were carried out across exceptional datasets together with Twitter, product critiques, and movie critiques. The assessment of those algorithms become performed with admire to accuracy, precision, consider, and average performance. The effects confirmed that Naive Bayes achieved the best accuracy many of the four fashions and it outperformed the other models in maximum cases, with Logistic Regression being barely higher than Naive Bayes in some situations. All of the analyses indicate that Naive Bayes is the nice sentiment evaluation set of rules for social media textual content evaluation.