We live in our own bubbles with our own news preferences and biases, but
to what extent are you aware of your own?
This talk will use keyword data to visualise the biggest topics in news
and how they are linked to one another. I will explain my journey to
gather this data (from web scraping with Beautiful Soup to Natural
Language Processing techniques) and then discuss what tools Python
provides for visualising this as a graph.
We'll look at different news outlets and compare their graphs, helping
to identify how the media selectively reports news and can influence
society. Comparing these networks can also help us see any differences
between what we think is important and what is actually reported on.
I would like to work with open source projects to create a branch of the tree with all
of the best videos for your open source project. Please
send me an email if you are interested.