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We analyze bias in historical corpora as encoded in diachronic distributionalsemantic models by focusing on two specific forms of bias, namely a political(i.e., anti-communism) and racist (i.e., antisemitism) one. For this, we use anew corpus of German parliamentary proceedings, DeuPARL, spanning the period1867--2020. We complement this analysis of historical biases in diachronic wordembeddings with a novel measure of bias on the basis of term co-occurrences andgraph-based label propagation. The results of our bias measurements align withcommonly perceived historical trends of antisemitic and anti-communist biasesin German politics in different time periods, thus indicating the viability ofanalyzing historical bias trends using semantic spaces induced from historicalcorpora.

Diachronic Analysis of German Parliamentary Proceedings: Ideological Shifts through the Lens of Political Biases