{"id":18794306,"url":"https://github.com/abhipatel35/twitter-analysis","last_synced_at":"2026-07-19T03:39:37.835Z","repository":{"id":214113585,"uuid":"735713441","full_name":"abhipatel35/Twitter-Analysis","owner":"abhipatel35","description":"Python script conducts sentiment analysis on Twitter data via GetOldTweets3, omitting NLTK. 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It then preprocesses the text data, cleans it by removing punctuations and stop words, and conducts sentiment analysis using a predefined sentiment lexicon.\n\n## Technologies Used\n\n- Python\n- GetOldTweets3 Library\n- Matplotlib Library\n\n## Getting Started\n\nTo use this script:\n\n1. Install the required libraries. You can install them via `pip`:\n\n    ```bash\n    pip install GetOldTweets3 matplotlib\n    ```\n\n2. Clone the repository:\n\n    ```bash\n    git clone https://github.com/abhipatel35/Twitter-Analysis.git\n    ```\n\n3. Run the script by executing:\n\n    ```bash\n    python main.py\n    ```\n\n## Acknowledgments\n\nThe script utilizes the [GetOldTweets3](https://github.com/Mottl/GetOldTweets3) library by Mottl to access historical tweets based on specified search criteria.\n\n## Results\n\nThe script generates a bar graph illustrating the sentiment distribution among the collected tweets. Additionally, the sentiment analysis results are printed to the console.\n\n## File Structure\n\n- `main.py`: Python script containing the code for data collection and sentiment analysis.\n- `sentiments.txt`: File containing sentiment lexicon or word sentiment associations.\n- `graph.png`: Generated bar graph showing the sentiment distribution among the tweets.\n\n---\n\nFeel free to adjust and expand upon this content to better suit your project's specifics and provide more detailed instructions or explanations if needed.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhipatel35%2Ftwitter-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhipatel35%2Ftwitter-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhipatel35%2Ftwitter-analysis/lists"}