COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021)

Anda Rozukalne; Vineta Kleinberga; Normunds Grūzītis

doi:10.17770/etr2021vol2.6564

COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021)

Anda Rozukalne, Vineta Kleinberga, Normunds Grūzītis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Abstract

This research focuses on the interrelation between news content on COVID-19 of three largest online news sites in Latvia (delfi.lv, apollo.lv, tvnet.lv) and the audience reaction to the news in the Latvian and Russian channels during the state of emergency. By using a tool for audience behaviour analysis, the Index of the Internet Aggressiveness (IIA), for analysis of audience comments, the study aims to uncover how and whether news about COVID-19 affect the level of audience aggressiveness. The study employs two data collection methods: news content analysis and IIA data analysis, in which ten index peaks are selected in each of the two emergency periods (spring 2020, fall and winter 2020/21). The study data consists of content analysis of 400 news items and analysis of ~80,000 comments, identifying the level of aggressiveness, the number and structure of comment keywords. The results show that the level of public aggressiveness is only partially formed by the attitude towards COVID-19 news: less than half of the most aggressively commented news is devoted to information about COVID-19. An increase in the level of aggressiveness of the audience of online news sites can be observed at the end of 2020 and at the beginning of 2021 when it is higher than over the course of 2020.

IIA is an online comment analysis platform, which analyses user-generated comments on news on online news sites according to pre-selected keywords, allowing to grasp the dynamics of commenters’ verbal aggressiveness. In addition, IIA exploits a machine learned classifier to recognize not only potentially aggressive keywords but also to analyse the entire comments. In January 2021, the IIA data set consists of ~24.89 million comments (~611.97 million words) added to ~1.34 million news articles.

Original language	English
Title of host publication	Vide. Tehnoloģija. Resursi : 13. starptautiskās zinātniski praktiskās konferences materiāli
Subtitle of host publication	Environment. Technology. Resources : Proceedings of the 13th International Scientific and Practical Conference
Place of Publication	Rēzekne
Publisher	Rēzeknes Tehnoloģiju akadēmija
Pages	141-147
Volume	2
DOIs	https://doi.org/10.17770/etr2021vol2.6564
Publication status	Published - 17 Jun 2021
Event	13th International Scientific and Practical Conference "Environment. Technology. Resources" - Rezekne, Latvia Duration: 17 Jun 2021 → 18 Jun 2021 Conference number: 13

Publication series

Name	Vide. Tehnologija. Resursi - Environment, Technology, Resources
ISSN (Print)	1691-5402

Conference

Conference	13th International Scientific and Practical Conference "Environment. Technology. Resources"
Country/Territory	Latvia
City	Rezekne
Period	17/06/21 → 18/06/21

Field of Science*

5.6 Political science
5.8 Media and Communication

Publication Type*

3.1. Articles or chapters in proceedings/scientific books indexed in Web of Science and/or Scopus database

Access to Document

10.17770/etr2021vol2.6564Licence: CC BY

COVID-19 News and AudienceFinal published version, 245 KBLicence: CC BY

Cite this

Rozukalne, A., Kleinberga, V., & Grūzītis, N. (2021). COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021). In Vide. Tehnoloģija. Resursi : 13. starptautiskās zinātniski praktiskās konferences materiāli: Environment. Technology. Resources : Proceedings of the 13th International Scientific and Practical Conference (Vol. 2, pp. 141-147). (Vide. Tehnologija. Resursi - Environment, Technology, Resources). Rēzeknes Tehnoloģiju akadēmija. https://doi.org/10.17770/etr2021vol2.6564

Rozukalne, Anda ; Kleinberga, Vineta ; Grūzītis, Normunds. / COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021). Vide. Tehnoloģija. Resursi : 13. starptautiskās zinātniski praktiskās konferences materiāli: Environment. Technology. Resources : Proceedings of the 13th International Scientific and Practical Conference. Vol. 2 Rēzekne : Rēzeknes Tehnoloģiju akadēmija, 2021. pp. 141-147 (Vide. Tehnologija. Resursi - Environment, Technology, Resources).

@inproceedings{4e475726f430460d9e949acf33beea3b,

title = "COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021)",

abstract = "This research focuses on the interrelation between news content on COVID-19 of three largest online news sites in Latvia (delfi.lv, apollo.lv, tvnet.lv) and the audience reaction to the news in the Latvian and Russian channels during the state of emergency. By using a tool for audience behaviour analysis, the Index of the Internet Aggressiveness (IIA), for analysis of audience comments, the study aims to uncover how and whether news about COVID-19 affect the level of audience aggressiveness. The study employs two data collection methods: news content analysis and IIA data analysis, in which ten index peaks are selected in each of the two emergency periods (spring 2020, fall and winter 2020/21). The study data consists of content analysis of 400 news items and analysis of ~80,000 comments, identifying the level of aggressiveness, the number and structure of comment keywords. The results show that the level of public aggressiveness is only partially formed by the attitude towards COVID-19 news: less than half of the most aggressively commented news is devoted to information about COVID-19. An increase in the level of aggressiveness of the audience of online news sites can be observed at the end of 2020 and at the beginning of 2021 when it is higher than over the course of 2020.IIA is an online comment analysis platform, which analyses user-generated comments on news on online news sites according to pre-selected keywords, allowing to grasp the dynamics of commenters{\textquoteright} verbal aggressiveness. In addition, IIA exploits a machine learned classifier to recognize not only potentially aggressive keywords but also to analyse the entire comments. In January 2021, the IIA data set consists of ~24.89 million comments (~611.97 million words) added to ~1.34 million news articles. ",

author = "Anda Rozukalne and Vineta Kleinberga and Normunds Grūzītis",

note = "Funding Information: ACKNOWLEDGEMENTS This study was supported by the Ministry of Education and Science, Republic of Latvia, as part of the project “Life with COVID-19: Evaluation of overcoming the coronavirus crisis in Latvia and recommendations for societal resilience in the future” [grant number VPP-COVID-2020/1-0013]. Publisher Copyright: {\textcopyright} 2021 Anda Rozukalne, Vineta Kleinberga, Normunds Grūzītis. Published by Rezekne Academy of Technologies.; 13th International Scientific and Practical Conference {"}Environment. Technology. Resources{"} ; Conference date: 17-06-2021 Through 18-06-2021",

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doi = "10.17770/etr2021vol2.6564",

language = "English",

volume = "2",

series = "Vide. Tehnologija. Resursi - Environment, Technology, Resources",

publisher = "Rēzeknes Tehnoloģiju akadēmija",

pages = "141--147",

booktitle = "Vide. Tehnoloģija. Resursi : 13. starptautiskās zinātniski praktiskās konferences materiāli",

address = "Latvia",

}

Rozukalne, A , Kleinberga, V & Grūzītis, N 2021, COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021). in Vide. Tehnoloģija. Resursi : 13. starptautiskās zinātniski praktiskās konferences materiāli: Environment. Technology. Resources : Proceedings of the 13th International Scientific and Practical Conference. vol. 2, Vide. Tehnologija. Resursi - Environment, Technology, Resources, Rēzeknes Tehnoloģiju akadēmija, Rēzekne, pp. 141-147, 13th International Scientific and Practical Conference "Environment. Technology. Resources", Rezekne, Latvia, 17/06/21. https://doi.org/10.17770/etr2021vol2.6564

COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021). / Rozukalne, Anda ; Kleinberga, Vineta; Grūzītis, Normunds.

Vide. Tehnoloģija. Resursi : 13. starptautiskās zinātniski praktiskās konferences materiāli: Environment. Technology. Resources : Proceedings of the 13th International Scientific and Practical Conference. Vol. 2 Rēzekne : Rēzeknes Tehnoloģiju akadēmija, 2021. p. 141-147 (Vide. Tehnologija. Resursi - Environment, Technology, Resources).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021)

AU - Rozukalne, Anda

AU - Kleinberga, Vineta

AU - Grūzītis, Normunds

N1 - Conference code: 13

PY - 2021/6/17

Y1 - 2021/6/17

N2 - This research focuses on the interrelation between news content on COVID-19 of three largest online news sites in Latvia (delfi.lv, apollo.lv, tvnet.lv) and the audience reaction to the news in the Latvian and Russian channels during the state of emergency. By using a tool for audience behaviour analysis, the Index of the Internet Aggressiveness (IIA), for analysis of audience comments, the study aims to uncover how and whether news about COVID-19 affect the level of audience aggressiveness. The study employs two data collection methods: news content analysis and IIA data analysis, in which ten index peaks are selected in each of the two emergency periods (spring 2020, fall and winter 2020/21). The study data consists of content analysis of 400 news items and analysis of ~80,000 comments, identifying the level of aggressiveness, the number and structure of comment keywords. The results show that the level of public aggressiveness is only partially formed by the attitude towards COVID-19 news: less than half of the most aggressively commented news is devoted to information about COVID-19. An increase in the level of aggressiveness of the audience of online news sites can be observed at the end of 2020 and at the beginning of 2021 when it is higher than over the course of 2020.IIA is an online comment analysis platform, which analyses user-generated comments on news on online news sites according to pre-selected keywords, allowing to grasp the dynamics of commenters’ verbal aggressiveness. In addition, IIA exploits a machine learned classifier to recognize not only potentially aggressive keywords but also to analyse the entire comments. In January 2021, the IIA data set consists of ~24.89 million comments (~611.97 million words) added to ~1.34 million news articles.

AB - This research focuses on the interrelation between news content on COVID-19 of three largest online news sites in Latvia (delfi.lv, apollo.lv, tvnet.lv) and the audience reaction to the news in the Latvian and Russian channels during the state of emergency. By using a tool for audience behaviour analysis, the Index of the Internet Aggressiveness (IIA), for analysis of audience comments, the study aims to uncover how and whether news about COVID-19 affect the level of audience aggressiveness. The study employs two data collection methods: news content analysis and IIA data analysis, in which ten index peaks are selected in each of the two emergency periods (spring 2020, fall and winter 2020/21). The study data consists of content analysis of 400 news items and analysis of ~80,000 comments, identifying the level of aggressiveness, the number and structure of comment keywords. The results show that the level of public aggressiveness is only partially formed by the attitude towards COVID-19 news: less than half of the most aggressively commented news is devoted to information about COVID-19. An increase in the level of aggressiveness of the audience of online news sites can be observed at the end of 2020 and at the beginning of 2021 when it is higher than over the course of 2020.IIA is an online comment analysis platform, which analyses user-generated comments on news on online news sites according to pre-selected keywords, allowing to grasp the dynamics of commenters’ verbal aggressiveness. In addition, IIA exploits a machine learned classifier to recognize not only potentially aggressive keywords but also to analyse the entire comments. In January 2021, the IIA data set consists of ~24.89 million comments (~611.97 million words) added to ~1.34 million news articles.

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M3 - Conference contribution

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T3 - Vide. Tehnologija. Resursi - Environment, Technology, Resources

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BT - Vide. Tehnoloģija. Resursi : 13. starptautiskās zinātniski praktiskās konferences materiāli

PB - Rēzeknes Tehnoloģiju akadēmija

CY - Rēzekne

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Y2 - 17 June 2021 through 18 June 2021

ER -

Rozukalne A , Kleinberga V, Grūzītis N. COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021). In Vide. Tehnoloģija. Resursi : 13. starptautiskās zinātniski praktiskās konferences materiāli: Environment. Technology. Resources : Proceedings of the 13th International Scientific and Practical Conference. Vol. 2. Rēzekne: Rēzeknes Tehnoloģiju akadēmija. 2021. p. 141-147. (Vide. Tehnologija. Resursi - Environment, Technology, Resources). doi: 10.17770/etr2021vol2.6564

COVID-19 News and Audience Aggressiveness: Analysis of News Content and Audience Reaction During the State of Emergency in Latvia (2020–2021)

Abstract

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