Amazon Machine Learning vs. Microsoft Azure Machine Learning as Platforms for Sentiment Analysis

Abstract

Recently, there has been an increasing attention towards the use machine learning platforms notably Amazon Machine learning and Microsoft Azure Machine learning (ML) to undertake sentiment analysis. The present experimental study compared Amazon ML against Microsoft Azure ML as platforms for performing sentiment analysis. The evaluation was done d using the evaluation metrics: accuracy, reliability, precision, F-score and Recall. Data was sourced from Twitter a microblogging platform. The sentiment analytics model was created based on Logistic regression analysis algorithms. Results confirmed that Microsoft Azure ML is more accurate and precise than Amazon ML as platforms for Sentiment Analysis and that Azure could be used reliably, accurately and securely to build Sentiment Analysis models for social media sites.