prikaz prve stranice dokumenta Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing
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Scientific paper - Original scientific paper
Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing
JMIR Public Health and Surveillance, 7 (2021), 12; e31540--. https://doi.org/10.2196/31540
Beliga, Slobodan; Martinčić-Ipšić, Sanda; Matešić, Mihaela; Petrijevčanin Vuksanović, Irena; Meštrović, Ana

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Beliga, S., Martinčić Ipšić, S., Matešić, M., Petrijevčanin Vuksanović, I. & Meštrović, A. (2021). Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing. JMIR Public Health and Surveillance, 7. (12), e31540--. doi: 10.2196/31540

Beliga, Slobodan, et al. "Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing." JMIR Public Health and Surveillance, vol. 7, no. 12, 2021, pp. e31540--. https://doi.org/10.2196/31540

Beliga, Slobodan, Sanda Martinčić Ipšić, Mihaela Matešić, Irena Petrijevčanin Vuksanović and Ana Meštrović. "Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing." JMIR Public Health and Surveillance 7, no. 12 (2021): e31540--. https://doi.org/10.2196/31540

Beliga, S., et al. (2021) 'Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing', JMIR Public Health and Surveillance, 7(12), pp. e31540--. doi: 10.2196/31540

Beliga S, Martinčić Ipšić S, Matešić M, Petrijevčanin Vuksanović I, Meštrović A. Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing. JMIR Public Health and Surveillance [Internet]. 2021 [cited 2024 October 23];7(12):e31540--. doi: 10.2196/31540

S. Beliga, S. Martinčić Ipšić, M. Matešić, I. Petrijevčanin Vuksanović and A. Meštrović, "Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing", JMIR Public Health and Surveillance, vol. 7, no. 12, pp. e31540--, 2021. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:195:647995. [Accessed: 23 October 2024]

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Metadata
Title (english)Infoveillance of the Croatian Online Media During the COVID-19 Pandemic: One-Year Longitudinal Study Using Natural Language Processing
AuthorSlobodan Beliga
AuthorSanda Martinčić-Ipšić
AuthorMihaela Matešić
AuthorIrena Petrijevčanin Vuksanović
AuthorAna Meštrović
Author's institutionUniversity of Rijeka
(Faculty of Informatics and Digital Technologies)
Author's institutionUniversity of Rijeka
Faculty of Humanities and Social Sciences
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Scientific / art field,
discipline and subdiscipline		BIOMEDICINE AND HEALTHCARE
Public Health and Health Care
Abstract (english)
Background: Online media play an important role in public health emergencies and serve as essential communication platforms. Infoveillance of online media during the COVID-19 pandemic is an important step toward gaining a better understanding of crisis communication. Objective: The goal of this study was to perform a longitudinal analysis of the COVID-19–related content on online media based on natural language processing. Methods: We collected a data set of news articles published by Croatian online media during the first 13 months of the pandemic. First, we tested the correlations between the number of articles and the number of new daily COVID-19 cases. Second, we analyzed the content by extracting the most frequent terms and applied the Jaccard similarity coefficient. Third, we compared the occurrence of the pandemic-related terms during the two waves of the pandemic. Finally, we applied named entity recognition to extract the most frequent entities and tracked the dynamics of changes during the observation period. Results: The results showed no significant correlation between the number of articles and the number of new daily COVID-19 cases. Furthermore, there were high overlaps in the terminology used in all articles published during the pandemic with a slight shift in the pandemic-related terms between the first and the second waves. Finally, the findings indicate that the most influential entities have lower overlaps for the identified people and higher overlaps for locations and institutions. Conclusions: Our study shows that online media have a prompt response to the pandemic with a large number of COVID-19–related articles. There was a high overlap in the frequently used terms across the first 13 months, which may indicate the narrow focus of reporting in certain periods. However, the pandemic-related terminology is well-covered.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleJMIR Public Health and Surveillance
Numberingvol. 7, no. 12, pp. e31540--
p-ISSN2369-2960
DOIhttps://doi.org/10.2196/31540
URN:NBNurn:nbn:hr:195:647995
Publication2021
ProjectNumber: IP-CORONA-2020-04-2061
Title (croatian): Višeslojni okvir za karakterizaciju širenja informacija putem društvenih medija tijekom krize COVID-19
Acronym: InfoCoV
Leader: Ana Meštrović
Jurisdiction: Croatia
Funding stream: IP-CORONA
Document URLhttps://publichealth.jmir.org/2021/12/e31540/
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2023-02-06 14:47:26