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| title: Twitter Sentiment Analysis | |
| emoji: ⚡ | |
| colorFrom: purple | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 4.37.2 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # Twitter Sentiment Analysis | |
| This project implements a sentiment analysis model to predict the sentiment (positive or negative) of tweets. An LSTM-based model has been trained on 1.6 million tweets. | |
| ## Project Structure | |
| - __01. Data Preparation:__ | |
| * `Data Collection`: The dataset consisting 1.6 million tweets has been collected from [here](https://www.kaggle.com/datasets/kazanova/sentiment140). | |
| * `Data Cleaning & Preprocessing`: | |
| - Removed stopwords | |
| - Applied Lemmatization | |
| - Vectorized the lemmatized data utilizing "TextVectorization" from keras | |
| - Saved the Vectorizer for utilizing later in the app | |
| - __02. Model Training:__ | |
| * A Bidirectional LSTM model with an embedding layer has been trained on the preprocessed data. | |
| - __03. App Deployment:__ | |
| * Developed a web-app with Gradio interface | |
| * Deployed the [App](https://huggingface.co/spaces/mazed/twitter_sentiment_analysis) in HuggingFace Spaces | |
| - `requirements.txt`: Contains the dependencies needed for the project: | |
| - `pandas` | |
| - `tensorflow==2.15.0` | |
| - `nltk` | |
| - `gradio` | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |