Examining Sentiment in Complex Texts. A Comparison of Different Computational Approaches
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DOI: 10.3389/fdata.2022.886362
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References listed on IDEAS
- Rice, Douglas R. & Zorn, Christopher, 2021. "Corpus-based dictionaries for sentiment analysis of specialized vocabularies," Political Science Research and Methods, Cambridge University Press, vol. 9(1), pages 20-35, January.
- Lauderdale, Benjamin E. & Herzog, Alexander, 2016. "Measuring Political Positions from Legislative Speech," Political Analysis, Cambridge University Press, vol. 24(3), pages 374-394, July.
- Ng, Weiyi & Leung, Ming D., 2015. "For love or money? Gender differences in how one approaches getting a job," Institute for Research on Labor and Employment, Working Paper Series qt41f0k4gd, Institute of Industrial Relations, UC Berkeley.
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Cited by:
- Bernhardt, Lea & Dewenter, Ralf & Thomas, Tobias, 2023.
"Measuring partisan media bias in US newscasts from 2001 to 2012,"
European Journal of Political Economy, Elsevier, vol. 78(C).
- Bernhardt, Lea & Dewenter, Ralf & Thomas, Tobias, 2020. "Measuring partisan media bias in US Newscasts from 2001-2012," Working Paper 183/2020, Helmut Schmidt University, Hamburg, revised 15 Nov 2022.
- Hugo Oriola & Matthieu Picault, 2023. "Opportunistic Political Central Bank Coverage: Does media coverage of ECB's Monetary Policy Impacts German Political Parties' Popularity?," EconomiX Working Papers 2023-30, University of Paris Nanterre, EconomiX.
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Keywords
sentiment analysis; German literature; dictionary; word embeddings; automated text analysis; computer-assisted text analysis; scaling method;All these keywords.
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