US Airline sentiment analysis using fine-tuned BERT
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Updated
Mar 22, 2022 - Jupyter Notebook
US Airline sentiment analysis using fine-tuned BERT
Sentiment analysis of US airline tweets using multiple approaches: lexicon-based (VADER, TextBlob), machine learning (Logistic Regression, Naive Bayes, Random Forest), and deep learning/transformer models (RNN, LSTM, GRU, BERT, RoBERTa, DistilBERT).
Interactive Streamlit dashboard for exploring sentiment patterns in Twitter data about US airlines, featuring dynamic visualizations, geospatial analysis, and word cloud generation.
A colab notebook in R containing sentiment analysis on US Airline tweets
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