The Polarity of Croatian Online News Related to COVID-19: A First Insight (CROSBI ID 709844)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Ilić, Anton ; Beliga, Slobodan
engleski
The Polarity of Croatian Online News Related to COVID-19: A First Insight
The polarity of online news publications thematically related to COVID-19 is analysed. A collection of sentiment annotations for news articles written in the Croatian language was created and compose a new Cro-CoV-Senti-articles-2020 dataset. The news article's sentiment is derived from the reactions of portal readers. In addition, well-known sentiment analysis approaches that use lexicons and machine learning algorithms have been implemented to automatically determine the sentiment of online news. Besides, the VADER framework was used in parallel. It has been found that for the purposes of crisis communication analysis when rapid analysis solutions are needed, existing tools can be used for preliminary sentiment analysis despite some technical shortcomings. However, for a more extensive analysis of the media space and highly valuable insights, some refinements are needed. This preliminary analysis, on a sample of approximately 3, 400 newspaper articles related to COVID-19, finds that readers perceive as many as two-thirds of articles negatively rather than positively.
sentiment analysis ; COVID-19 ; online news articles ; sentiment lexicon ; machine learning ; VADER
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Podaci o prilogu
237-246.
2021.
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objavljeno
Podaci o matičnoj publikaciji
Central European conference on information and intelligent systems
Vrček, Neven ; Pergler, Elisabeth ; Grd, Petra.
Varaždin: Fakultet organizacije i informatike Sveučilišta u Zagrebu
1847-2001
1848-2295
Podaci o skupu
32nd Central European Conference on Information and Intelligent Systems (CECIIS 2021)
predavanje
13.10.2021-15.10.2021
Varaždin, Hrvatska
Povezanost rada
Informacijske i komunikacijske znanosti, Računarstvo