Media Narrative Regarding Restrictions on Social Life During the COVID-19 Pandemic on Gazeta.pl

Krzysztof Flasiński

Abstrakt

The aim of this study was to describe how the gazeta.pl website newsroom conducted the media narrative regarding restrictions on social, professional and private life based on articles about the COVID-19 epidemic published on the website. The study covered the period from the 14th of January 2020 (publication of the first thematic text related to the epidemic) to the 20th of May 2020 (date of lifting of the requirement to wear face masks in outdoor settings). The research material comprised 16,414 news stories published on the gazeta.pl website in which the word coronavirus was used. The texts were classified into 12 thematic groups. Firstly, the research results indicate that the subject of the pandemic follows the principles of the life cycle of a news topic. In addition, a more detailed, five-phase version of the news topic life cycle concept was proposed. Secondly, no positive correlation was identified between the number of new stories on COVID-19 and the number of confirmed cases of the disease. Lastly, the correlation between the number and frequency of news stories on specific topics connected with COVID-19 was limited.

Słowa kluczowe: COVID-19, data analysis, journalism, news media, online communication
References

Boberg S., Quandt T., Schatto-Eckrodt T., Frischlich L. (2020). Pandemic Populism: Facebook Pages of Alternative News Media and the Corona Crisis. A Computational Content Analysis [https://arxiv.org/abs/2004.02566; 10.06.2020].

Casero-Ripollés A. (2020). Impact of COVID-19 on the Media System. Communicative and Democratic Consequences of News Consumption During the Outbreak. El Profesional de la Información, vol. 29(2) [https://doi.org/10.3145/epi.2020.mar.23; 10.06.2020].

Castillo C., El-Haddad M., Pfeffer J., Stempeck M. (2014). Characterizing the Life Cycle of Online News Stories Using Social Media Reactions. In: Proceedings of the 17th ACM conference on computer supported cooperative work & social computing, p. 211–223 [https://dl.acm.org/doi/abs/10.1145/2531602.2531623; 10.06.2020].

Chadwick A. (2011). The Political Information Cycle in a Hybrid News System: The British Prime Minister and the “Bullygate” Affair. The International Journal of Press/Politics, vol. 16(1), p. 3–29 [https://doi.org/10.1177/1940161210384730; 10.06.2020].

Chakraborty A., Ghosh S., Ganguly N., Gummadi K.P. (2019). Optimizing the Recency-Relevance-Diversity Trade-Offs in Non-Personalized News Recommendations. Information Retrieval Journal, vol. 22(5), p. 447–475 [https://link.springer.com/article/10.1007/s10791–019–09351–2; 10.06.2020].

Chen E., Lerman K., Ferrara E. (2020). Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set. JMIR Public Health Surveill, vol. 6(2) [https://publichealth.jmir.org/2020/2/e19273; 10.06.2020].

Cinelli M., Quattrociocchi W., Galeazzi A., Valensise C.M., Brugnoli E., Schmidt A.L., Zola P., Zollo F., Scala A. (2020). The COVID-19 Social Media Infodemic. New Media [https://arxiv.org/abs/2003.05004; 10.06.2020].

Dayan D., Katz E. (1992). Media Events: The Live Broadcasting of History. Cambridge.

Hepp A., Couldry N. (2010) Introduction: Media Events in Globalized Media Cultures. In: N. Couldry, A. Hepp (eds.). Media Events in a Global Age (p. 1–20). London.

Leskovec J., Backstrom L., Kleinberg J. (2009). Meme-Tracking and the Dynamics of the News Cycle. In: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, p. 497–506 [https://dl.acm.org/doi/abs/10.1145/1557019.1557077; 10.06.2020].

Li J., Xu Q., Cuomo R., Purushothaman V., Mackey T. (2020). Data Mining and Content Analysis of the Chinese Social Media Platform Weibo During the Early COVID-19 Outbreak: Retrospective Observational Infoveillance Study. JMIR Public Health and Surveillance, vol. 6(2) [https://publichealth.jmir.org/2020/2/e18700; 10.06.2020].

Liebes T. (1998) Television’s Disaster Marathons. A Danger for Democratic Processes? In: T. Liebes, J. Curran (eds.). Media, Ritual and Identity (p. 71–84). London.

Messner M., Distaso M.W. (2008). The Source Cycle: How Traditional Media and Weblogs Use Each Other as Sources. Journalism Studies, vol. 9(3), p. 447–463.

Molotch H., Lester, M. (1974). News as Purposive Behavior: On the Strategic Use of Routine Events, Accidents, and Scandals. American Sociological Review, vol. 39(1), p. 101–112 [https://doi.org/10.2307/2094279; 10.06.2020].

Oosterhoff B., Palmer C. (2020). Psychological Correlates of News Monitoring, Social Distancing, Disinfecting, and Hoarding Behaviors among US Adolescents during the COVID-19 Pandemic [https://doi.org/10.31234/osf.io/rpcy4; 10.06.2020].

PBI (2020). Polski internet w maju 2020. Badanie Gemius PBI [http://pbi.org.pl/badanie-gemius-pbi/polski-internet-w-maju-2020; 10.06.2020].

Schlesinger P. (1977). Newsmen and Their Time-Machine. The British Journal of Sociology, vol. 28(3), p. 336a350 [https://doi.org/10.2307/589998].

Sumiala J., Tikka M., Huhtamäki J., Valaskivi K. (2016). #JeSuisCharlie: Towards a Multi-Method Study of Hybrid Media Events. Media and Communication, vol. 4(4), p. 97–108.

Yang J. (2009). Analyzing the Temporal Dynamics of the News Cycle [http://snap.stanford.edu/class/cs224w-2010/proj2009/Memetracker_final.pdf; 10.06.2020].

ZKDP (2020). Kwiecień 2020. Dane dzienników [https://www.teleskop.org.pl/zkdp; 10.06.2020].

Czasopismo ukazuje się w sposób ciągły on-line.
Pierwotną wersją czasopisma jest wersja elektroniczna publikowana w internecie.