Sentiment Analysis in Twitter
Sarwesh Tekale, Arpan Shinde, Sumeet Sonawane, Arnaw Dwivedi, I Boguslavsky, A Pak, P Paroubek, J Scott, H Wang, B Pang, L Lee, T Wilson, B Liu
2023International Research Journal of Modernization in Engineering Technology and Science131 citationsDOIOpen Access PDF
Abstract
In the ever-expanding realm of the internet, where vast amounts of data are generated daily, platforms like Twitter become hubs for expressing opinions.This survey delves into sentiment analysis on Twitter, focusing on the challenges posed by unstructured, diverse opinions.Leveraging natural language processing (NLP) techniques, a robust sentiment analysis framework is constructed.The framework utilizes machine learning algorithms such as Naive Bayes, Maximum Entropy, and Support Vector Machine (SVM).A diverse dataset is collected, preprocessed, and used to train and evaluate the model.
Topics & Concepts
MicrobloggingSocial mediaComputer scienceSentiment analysisWorld Wide WebService (business)Simple (philosophy)Information retrievalData scienceNatural language processingArtificial intelligenceEconomyPhilosophyEconomicsEpistemologySentiment Analysis and Opinion MiningAdvanced Text Analysis TechniquesComplex Network Analysis Techniques