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cs.CL2025
Analyzing German Parliamentary Speeches: A Machine Learning Approach for Topic and Sentiment Classification
Lukas Pätz, Moritz Beyer, Jannik Späth +4
This study investigates political discourse in the German parliament, the Bundestag, by analyzing approximately 28,000 parliamentary speeches from the last five years. Two machine…
cs.LG2025
Overcoming Algorithm Aversion with Transparency: Can Transparent Predictions Change User Behavior?
Lasse Bohlen, Sven Kruschel, Julian Rosenberger +2
Previous work has shown that allowing users to adjust a machine learning (ML) model's predictions can reduce aversion to imperfect algorithmic decisions. However, these results wer…