thu
1
11:10 – 11:55
Talk
Data
Data Your Data Has an Agenda: Forecasting Elections When the Polls Take Sides
Viktor Tisza
Creator of the open-source election forecast engine Kronikas at Diligent
Every forecast is a bet on which data to trust, and that bet gets harder when the polls themselves become campaign weapons. This talk explains how a hierarchical Bayesian model forecasts elections: it tracks how opinion drifts, learns each pollster’s systematic bias, and turns conflicting surveys into probabilities with honest uncertainty. The case study is Hungary’s 2026 election, where SzazKilencvenKilenc (199), an independent poll aggregator, used it to forecast all 199 seats in parliament. Its engine, Kronikas, is now open source and already powering forecasts for elections internationally. We close with where polling is heading, and why the same approach works anywhere business data sources disagree.