Topic modelling and sentiment analysis of COVID-19 related news on Croatian Internet portal (CROSBI ID 707970)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Buhin Pandur, Maja ; Dobša, Jasminka ; Beliga, Slobodan ; Meštrović, Ana
engleski
Topic modelling and sentiment analysis of COVID-19 related news on Croatian Internet portal
The research aims to identify topics and sentiments related to the COVID-19 pandemic in Croatian online news media. For analysis, we used news related to the COVID-19 pandemic from the Croatian portal Tportal.hr published from 1st January 2020 to 19th February 2021. Topic modelling was conducted by using the LDA method, while dominant emotions and sentiments related to extracted topics were identified by National Research Council Canada (NRC) word-emotion lexicon created originally for English and translated into Croatian, among other languages. We believe that the results of this research will enable a better understanding of the crisis communication in the Croatian media related to the COVID-19 pandemic.
news media ; sentiment ; emotions ; pandemic ; lexicon approach ; Latent Dirichlet Allocation
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Podaci o prilogu
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2021.
objavljeno
Podaci o matičnoj publikaciji
Proceeding of Conference on Data Mining and Data Warehouses 2021
Grobelnik, Marko ; Mladenić, Dunja
Ljubljana:
Podaci o skupu
Slovenian KDD Conference on Data Mining and Data Warehouses (SiKDD 2022)
predavanje
04.10.2021-04.10.2021
Ljubljana, Slovenija
Povezanost rada
Informacijske i komunikacijske znanosti, Interdisciplinarne društvene znanosti