Train Crowdedness Prediction | Improving Decisionmaking in Voting & Education

We are excited to host this in-person meetup to kick off the new year!

The venue is GoDataDriven HQ, Wibautstraat 202 in Amsterdam. Food will be served starting at 18:00 with the first talk starting at 18:45.

We have two great speakers for this event, see below for more information. We are looking forward to seeing you in person soon!
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Title: Train crowdedness predictions

Abstract: The Dutch railways (NS) aims to provide sustainable mobility for everybody. One key requirements for a pleasant journey is a seat to sit on. In this talk we’ll discuss how the short term crowdedness is predicted. This prediction is shown in the app/website as a crowdedness indicator (‘druktepoppetjes’) and is used for last minute changes in the train composition.

Bio: Tjebbe Hepkema did his BSc and MSc in mathematics and subsequently obtained his PhD in physics investigating the dynamics of tides and sandbars. He now works as a data scientist for the dutch railways (NS).

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Title: Joy in Choices? Decision Intelligence Tools to aid with informed Decisionmaking

Abstract: Overwhelming, a privilege, a burden, time-pressed guesses made while stressed — choices can be many things, and many of them are unpleasant. Yet, every day people have to make them. Most often we have to choose based on either incomplete or insurmountable amounts of informations related to the decision at hand. But there is help: Decision Intelligence Tools that give users an orientation in the thicket of important choices. In this talk, I will discuss two such products – Vote Compass and DegreeHub – which inform people about their choices in two fields: political actors to vote for and postsecondary education to attend. To do so, these tools rely on the power of Data Science to reduce complexity while maintaining nuance. My talk will discuss assumptions, data sources, approaches, and limitations of either.

Bio: Alexander Beyer is a computational social scientist who is fascinated by the power of data to increase social participation and civic engagement. He studied in Tübingen (Germany), Geneva (NY), as well as Vancouver (BC), and received training at the University of Essex and European Consortium for Political Research’s summer schools. He holds a PhD in Political Science from Simon Fraser University, where his research focused on support for Radical Right Parties in Western Europe. Alex’s methodological expertise includes Bayesian inference, multi-level modelling, network analysis, and text-as-data approaches.