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Machine Learning Final Project - Sensing Bots on Social Media
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Readme.md

This Project in Machine Learning is aimed at detecting whether a twitter profile is bot or not. Starting with feature extraction, we checked the test accuracy of various models like Multinomial Naive Bayes, Decision Trees, and Random Forest.

Finally, we chose Random Forest Classifier for the task which gave us an test accuracy over 90% in detecting bots.

The class also took part in a kaggle competition (https://www.kaggle.com/c/twitter-bot-classification) in which various teams took part and our model secured the third position.

To see the model in action, run the BotDetection.py file located in FinalCode directory with the following command:

python BotDetection.py (Dependencies: Python 3, conda)

To understand the reasoning behind choosing features and the model, check the FinalProject.ipynb file in FinalCode directory.

MIT License

Copyright (c) 2017

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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