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Validating a sentiment dictionary for German political language—a workbench note

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  • Rauh, Christian

Abstract

Automated sentiment scoring offers relevant empirical information for many political science applications. However, apart from English language resources, validated dictionaries are rare. This note introduces a German sentiment dictionary and assesses its performance against human intuition in parliamentary speeches, party manifestos, and media coverage. The tool published with this note is indeed able to discriminate positive and negative political language. But the validation exercises indicate that positive language is easier to detect than negative language, while the scores are numerically biased to zero. This warrants caution when interpreting sentiment scores as interval or even ratio scales in applied research.

Suggested Citation

  • Rauh, Christian, 2018. "Validating a sentiment dictionary for German political language—a workbench note," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(4), pages 319-343.
    • Handle: RePEc:zbw:espost:180851
    DOI: 10.1080/19331681.2018.1485608
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    References listed on IDEAS

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    Cited by:

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    2. Garz, Marcel & Sörensen, Jil & Stone, Daniel F., 2020. "Partisan selective engagement: Evidence from Facebook," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 91-108.
    3. Koop, Christel & Scotto di Vettimo, Michele, 2023. "How do the media scrutinise central banking? Evidence from the Bank of England," European Journal of Political Economy, Elsevier, vol. 77(C).
    4. Ozgun, Burcu & Broekel, Tom, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Technological Forecasting and Social Change, Elsevier, vol. 167(C).

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