Sentiment analysis of twitter data using machine learning approaches and semantic analysis

By Geetika Gautam, Divakar Yadav. International Conference on Contemporary Computing, 2014

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Classification of sentiment reviews using n-gram machine learning approach (2016, methodology): “In supervised learning technique, the dataset is labeled and thus, trained to obtain a reasonable output which help in proper decision making (Gautam & Yadav, 2014).”
Machine Learning-Based Sentiment Analysis for Twitter Accounts (2018, methodology): “Although a lot of work has been done to analyze tweet sentiments by applying techniques of machine learning [2,41], the work of [42] was based on a set of techniques of machine learning that were Naïve Bayesian, SVM [43] and entropy-based [44] along with semantic analyses to classify product…”