Arrangementer

Kommende

Bildet kan inneholde: rektangel, skrift, parallell, elektrisk blå, symmetri.
Tid og sted: 15. apr. 2021 10:0011:30, Zoom

Neil Ketchley presents Violence, Concessions, and Decolonization: Evidence from the 1919 Egyptian Revolution

 

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Polls
Tid og sted: 6. mai 2021 10:0011:30, Zoom

Opinion polls are not reported in the media as unfiltered numbers. And some opinion polls are not reported at all. This talk by Zoltán Fazekas from Copenhagen Business School is about how polls travel through several stages that eventually turn boring numbers into biased news. The theoretical framework describes how and why opinion polls that are available to the public are more likely to focus on change, despite most polls showing little to no change. These dynamics are empirically demonstrated using several data sources and measurements from two different democracies (Denmark and the U.K.) covering several years of political reporting. In the end, a change narrative will be prominent in the reporting of opinion polls which contributes to what the general public sees and shares, further consolidating a picture of volatile political competition.

Arabisk tekst som bilde
Tid og sted: 17. juni 2021 10:0011:30, Nydalen / Zoom

Optical character recognition (OCR) promises to open vast bodies of historical data to scientific inquiry, but OCR can be cumbersome when documents are noisy. The past 18 months have seen the launch of new OCR processors with vastly improved accuracy. In this seminar, Thomas Hegghammer will give an overview of the latest tools and present a new R package that offers access to the most powerful of them all, Google Document AI.

Tidligere

Tid og sted: 11. mars 2021 10:0011:30, Zoom / 830

Hvem vinner stortingsvalget? Selv om ingen vet noe sikkert før valget har funnet sted, har vi en mengde data som gjør det mulig å svare i form av sannsynligheter.

Tid og sted: 18. feb. 2021 10:0011:30, Zoom / 830

Philipp Broniecki presents joint work with Lucas Leeman and Reto Wüest on an R-package for Improved multilevel regression with post-stratification through machine learning (autoMrP)