Spread of Covid-19 information in Latvia: who leads and who follows?

The outbreak of the coronavirus disease (COVID-19) at the end of December 2019 has led to substantial discussions in traditional media as well as in social networks. The understanding of the diffusion of information about the COVID-19 can help government officials and researchers to obtain better understanding of public concerns as well as to prevent the rapid spread of misinformation. We address the question of the diffusion of information about the COVID-19 with a big data analysis of social media posts and news media articles. This paper is an analysis of public conversations in social media, specifically Twitter, and traditional news online media during the first outbreak of COVID-19 in Latvia. Using the computer assisted text analysis, we examined the dominant frames of public discussions and investigated the extent to which social media content may bypass, follow and attract attention of traditional media. For the search of information regarding COVID-19, we derived a set of twelve key identifying terms and phrases in Latvian. We compiled more than 46 thousand tweets and more 45 thousand news articles for the period from March 2020 when the state of emergency was declared to 10 June 2020 when the state of emergency was lifted. To identify common frames and to describe how the prevalence of these changes took place over time, the comprehensive codebook of 11 dominant frames, 31 major topics and 160 subtopics was designed. We utilized big data to better understand the dynamics of political communication and to explore attention in traditional media and social media for COVID-19 related issues. We find evidence of time-series linkage run from social media to other social media, as well as from the social media to traditional media. Thus, we are able to conclude that the public discussions in traditional media and social media have causal linkage. This paper shows the potential of using social media to conduct “infodemic” studies for the planning of strategic communication. The methodology created in research can be used to track information diffusion and to analyse near real-time content, allowing public authorities to respond to public concerns more quickly.