Quantifying Polish Anti-semitism in Twitter: A Robust Unsupervised Approach with Signal Processing
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Anti-Semitism has long been a controversial topic in Poland, and remains so to the present day. Holocaust research continues in Poland today, attempting to face up to the truth about the nature and extent of any Polish complicity with the Nazis in the persecution and massacre of Jews during World War II. But such research faces significant headwinds in various forms, including popular Polish nationalism as well as the passage in 2018 by the current Polish nationalist government of a law against defaming the ‘Polish nation’ in connection with the Holocaust. A recent court case against a Poland-based Holocaust researcher again brought this to the fore, lighting up the Polish Twittersphere with chatter on the topic. In this paper, we set out to analyze this chatter, to shed light – not on any past Polish anti-Semitism – but on present-day Polish attitudes. Along the way, we argue that unsupervised techniques from signal processing are the ideal tool for wading into such a politically and emotionally charged topic. Such techniques simply reflect, in condensed and quantifiable form, what is in the data. It is then up to the human analyst to draw the appropriate conclusions.
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Link to article (paywalled), Quantifying Polish Anti-semitism in Twitter: A Robust Unsupervised Approach with Signal Processing
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Quantifying Polish Anti-semitism in Twitter: A Robust Unsupervised Approach with Signal Processing. . 2022: https://archive.jpr.org.uk/10.1007/978-3-030-96188-6_2
