| Autor: |
Orešković, Vedran, Meštrović, Ana, Beliga, Slobodan |
| Předmět: |
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| Zdroj: |
Central European Conference on Information & Intelligent Systems; 2023, p407-416, 10p |
| Abstrakt: |
In this study, a computational content analysis of crisis-related articles published in electronic media for two crises, namely COVID-19 and the Russia-Ukraine war, is conducted. A set of methods for content analysis is proposed, which involves the combination of exploratory analysis, main topic filtering, and performing named entity recognition enhanced with network analysis. The main finding of this study is a list of the most frequently mentioned persons, locations, and organizations in the news articles of both crises and how they are connected. The results obtained affirm the suitability of the proposed approach for crisis-related content analysis. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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