Illustrating the flexibility of Bayesian models: from cancer medicine to political tweets
The Bayesian paradigm provides a flexible way of thinking about data analysis problems. While there are standard foundationa land theoretical arguments for its use, this talk focuses on illustrating what it can bring to the table in practice. A particular practical benefit is providing a mathematically rigorous way to discover structure within the given data that is often critical in scientific research and downstream applications. I review two motivating examples from distinct fields. The first example deals with identifying a subset of variables that can be used to predict colon cancer progression, and that resulted in a patented system for colon cancer treatment. The second example deals with understanding the popularity dynamics of tweets made by politicians in European elections, with a focus on extreme right parties in Germany and France. Both examples benefit from the use of Bayesian regression and / or latent variable regression models, not only from a methodological point of view but also practically by simplifying the interpretation and downstream transferring of the results.
David Rosell Deptartment of Economics & Business, Universitat Pompeu Fabra, Spain.