An Unsupervised Learning Study on International Media Responses Bias to the War in Ukraine
Author:
Affiliation:
1. Department of Computational Linguistics , University of Zurich , Andreasstrasse 15 , 8050, Zurich , Switzerland
2. English Department, University of Zurich, Plattenstrasse 47, 8032 , Zurich , Switzerland
Abstract
Publisher
Walter de Gruyter GmbH
Link
https://www.degruyter.com/document/doi/10.1515/csh-2023-0010/pdf
Reference27 articles.
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2. Appiah-Otoo, I. 2023. “Russia–Ukraine War and US Oil Prices.” Energy Research Letters 4 (1): 1–5. https://doi.org/10.46557/001c.37691.
3. Barde, B. V., and A. M. Bainwad. 2017. “An Overview of Topic Modeling Methods and Tools.” In 2017 International Conference on Intelligent Computing and Control Systems (ICICCS), 745–50. Madurai: IEEE.
4. Behnassi, M., and M. El Haiba. 2022. “Implications of the Russia–Ukraine War for Global Food Security.” Nature Human Behaviour 6 (6): 754–5. https://doi.org/10.1038/s41562-022-01391-x.
5. Biktimirov, E. N., T. Sokolyk, and A. Ayanso. 2021. “Sentiment and Hype of Business Media Topics and Stock Market Returns during the COVID-19 Pandemic.” Journal of Behavioral and Experimental Finance 31: 100542. https://doi.org/10.1016/j.jbef.2021.100542.
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