Literature Review and Related Work

References

• Twitter Developer Resources - https://developer.twitter.com/
• We’d like to acknowledge and thank Onur Varol and his team’s research work on detecting Twitter bot. This learning was key for our execution approach.
  • “Online Human-Bot Interactions: Detection, Estimation, and Characterization”
  • Botometer - https://botometer.iuni.iu.edu/#!/
  • Bot repository - https://botometer.iuni.iu.edu/bot-repository/datasets.html
• For NLP topic analysis and modeling using spaCy, we would like to thank Susan Li and her website:
  • https://towardsdatascience.com/machine-learning-for-text-classification-using-spacy-in-python-b276b4051a49
• cresci-2017 data set - https://botometer.iuni.iu.edu/bot-repository/datasets/cresci-2017/cresci-2017.csv.zip
• Tweepy Python Library - http://www.tweepy.org/
• Text Blob - https://textblob.readthedocs.io/en/dev/#
• spaCy - https://spacy.io/
• NLTK - https://www.nltk.org/
• SciKit Learn - https://scikit-learn.org/
• Keras - https://keras.io/
• Seaborn - https://seaborn.pydata.org/