/Sentiment-analysis-based-on-Corona-Virus-tweet-using-Word2Vec

I performed sentiment analysis on coronavirus-related tweets from a Kaggle dataset, utilizing Word2Vec embeddings with ML models like XGBoost, SVM, Random Forest, and Logistic Regression. Model performance was evaluated using metrics like accuracy, confusion matrices, and classification reports to discern sentiment in the tweets.

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I performed sentiment analysis on coronavirus-related tweets from a Kaggle dataset, utilizing Word2Vec embeddings with ML models like XGBoost, SVM, Random Forest, and Logistic Regression. Model performance was evaluated using metrics like accuracy, confusion matrices, and classification reports to discern sentiment in the tweets.

Dataset link: https://www.kaggle.com/datasets/datatattle/covid-19-nlp-text-classification/data

Code Prepared by: Md. Injamul Haque (Dept. of CSE)