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.