prikaz prve stranice dokumenta Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model
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Scientific paper - Original scientific paper
Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model
Applied Sciences-Basel, 11 (2021), 21; https://doi.org/10.3390/app112110442
Babić, Karlo; Petrović, Milan; Beliga, Slobodan; Martinčić-Ipšić, Sanda; Matešić, Mihaela; Meštrović, Ana

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Babić, K., Petrović, M., Beliga, S., Martinčić Ipšić, S., Matešić, M. & Meštrović, A. (2021). Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model. Applied Sciences-Basel, 11. (21). doi: 10.3390/app112110442

Babić, Karlo, et al. "Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model." Applied Sciences-Basel, vol. 11, no. 21, 2021. https://doi.org/10.3390/app112110442

Babić, Karlo, Milan Petrović, Slobodan Beliga, Sanda Martinčić Ipšić, Mihaela Matešić and Ana Meštrović. "Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model." Applied Sciences-Basel 11, no. 21 (2021). https://doi.org/10.3390/app112110442

Babić, K., et al. (2021) 'Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model', Applied Sciences-Basel, 11(21). doi: 10.3390/app112110442

Babić K, Petrović M, Beliga S, Martinčić Ipšić S, Matešić M, Meštrović A. Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model. Applied Sciences-Basel [Internet]. 2021 [cited 2024 May 05];11(21). doi: 10.3390/app112110442

K. Babić, M. Petrović, S. Beliga, S. Martinčić Ipšić, M. Matešić and A. Meštrović, "Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model", Applied Sciences-Basel, vol. 11, no. 21, 2021. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:186:252651. [Accessed: 05 May 2024]

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Metadata
Title (english)Characterisation of COVID-19-Related Tweets in the Croatian Language: Framework Based on the Cro-CoV-cseBERT Model
AuthorKarlo Babić
AuthorMilan Petrović
AuthorSlobodan Beliga
AuthorSanda Martinčić-Ipšić
AuthorMihaela Matešić
AuthorAna Meštrović
Author's institutionUniversity of Rijeka
Faculty of Humanities and Social Sciences
Scientific / art field,
discipline and subdiscipline		HUMANISTIC SCIENCES
Interdisciplinary Humanistic Studies
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Abstract (english)
This study aims to provide insights into the COVID-19-related communication on Twitter in the Republic of Croatia. For that purpose, we developed an NL-based framework that enables automatic analysis of a large dataset of tweets in the Croatian language. We collected and analysed 206, 196 tweets related to COVID-19 and constructed a dataset of 10, 000 tweets which we manually annotated with a sentiment label. We trained the Cro-CoV-cseBERT language model for the representation and clustering of tweets. Additionally, we compared the performance of four machine learning algorithms on the task of sentiment classification. After identifying the best performing setup of NLP methods, we applied the proposed framework in the task of characterisation of COVID-19 tweets in Croatia. More precisely, we performed sentiment analysis and tracked the sentiment over time. Furthermore, we detected how tweets are grouped into clusters with similar themes across three pandemic waves. Additionally, we characterised the tweets by analysing the distribution of sentiment polarity (in each thematic cluster and over time) and the number of retweets (in each thematic cluster and sentiment class). These results could be useful for additional research and interpretation in the domains of sociology, psychology or other sciences, as well as for the authorities, who could use them to address crisis communication problems.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review
Publication versionPublished version
Journal titleApplied Sciences-Basel
Numberingvol. 11, no. 21, p. 0
e-ISSN2076-3417
DOIhttps://doi.org/10.3390/app112110442
URN:NBNurn:nbn:hr:186:252651
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
ProjectNumber: uniri-drustv-18-38
Title (croatian): Postupci mjerenja semantičke sličnosti tekstova
Title (english): Measuring the semantic similarity of texts
Acronym: SemText
Leader: Ana Meštrović
Jurisdiction: Croatia
Funding stream: Sveučilište u Rijeci
Document URLhttp://bib.irb.hr/1155753
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2022-12-20 10:22:09