Twitter-Sentiment-Analysis

We have worked over a Natural Language Problem namely Sentiment Analysis as a part of our Summer Research Internship (2022).
The Dataset used is from Kaggle
Under the guidance of Ms. Ritu Rani we were able to write a Research Paper which got shortlisted for ICICT-2022, an IEEE international conference.
We were privileged to have our Research Paper published on IEEE Xplore and Google Scholar : https://ieeexplore.ieee.org/document/10064505/keywords#keywords

Name		Name	Last commit message	Last commit date
Latest commit History 71 Commits
Confusion Matrices 2		Confusion Matrices 2
Confusion Matrices		Confusion Matrices
Research		Research
__pycache__		__pycache__
images		images
.gitignore		.gitignore
FinalSoultion.ipynb		FinalSoultion.ipynb
LOGISTIC REGRESSION IS BEST MODEL FOR SENTIMENT ANALYSIS .txt		LOGISTIC REGRESSION IS BEST MODEL FOR SENTIMENT ANALYSIS .txt
MainSolution-Copy1.ipynb		MainSolution-Copy1.ipynb
MainSolution-Copy2.ipynb		MainSolution-Copy2.ipynb
MainSolution-Copy3.ipynb		MainSolution-Copy3.ipynb
MainSolution.ipynb		MainSolution.ipynb
NaiveBayesTwitterScratch.ipynb		NaiveBayesTwitterScratch.ipynb
NaiveBayeswithoutTFiDF.ipynb		NaiveBayeswithoutTFiDF.ipynb
README.md		README.md
RNN.docx		RNN.docx
Untitled.ipynb		Untitled.ipynb
dictionaries.py		dictionaries.py
evaluating.py		evaluating.py
final_textual_data.txt		final_textual_data.txt
major-project-twitter-sentiment-analysis.ipynb		major-project-twitter-sentiment-analysis.ipynb
rnn_model.hdf5		rnn_model.hdf5

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