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Title : Racism Detection by Analyzing Differential Opinions Through Sentiment Analysis of Tweets Using Stacked Ensemble GCR-NN Model

Author : Katta Srinu, K.Vara Prasad, Dr.Mahendra, C.Archana

Abstract :

Every day, people utilize several social media sites to disseminate information about what's hot in the world. Twitter, in particular, is used extensively by individuals all over the globe to voice and disseminate their thoughts and ideas. This has a profound effect on many issues, and individuals do it to express their agreement or disagreement. Logistic Regression, Decision Tree, and XGBOOST from Machine Learning, and TF-IDF and Bag of Words from Natural Language Processing, are the five basic methodologies utilized when thinking about Twitter sentiment analysis. First, raw data is prepared for analysis, then a word cloud is constructed, features are extracted, and finally, a comparison of multiple Machine Learning models is generated. Preprocessing, visualization, and feature extraction are some of the most important aspects of machine learning. Preprocessing, visualization, and feature extraction are some of the most important aspec

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International Journal of Engineering Research & Informatics (IJERI)
E-ISSN: 2348-6481

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