by Roberto Rocha

What does a decade of news stories published on cbc.ca tell us about Canada? What words and ideas are associated with different cities, provinces, and public figures? Can it tell us who is Montreal's Drake or what is the Vancouver equivalent of poutine? Can it reveal unconscious biases? Are certain words more associated with the word 'man' than the word 'woman'? With 'black' versus 'white', 'indigenous', or 'immigrant'? In this talk, I'll show how I trained a neural word embedding model with hundreds of thousands of news stories using the gensim library and explored the word associations through a Jupyter notebook.

About the Author

Talk Details