The outbreak of the COVID-19 has led to substantial discussions in traditional media as well as in social networks. The understanding of the diffusion of information can help government officials to obtain a better understanding of public concerns as well as to prevent the rapid spread of misinformation. This article provides analysis of public conversations in Twitter and news online media during the first wave outbreak of COVID-19 in Latvia. Using computer-assisted text analysis, we examined the main themes and topical agendas of public discussions. The authors compiled more than 46 thousand tweets and 45 thousand news articles related to the COVID-19 during the first outbreak of virus. To identify common themes and to describe how the prevalence of these changes took place over time, the researchers manually created the project dictionary. The dictionary included 11 dominant themes, 31 major topics and 160 subtopics and 11 topical agendas. Human and computer coding was combined to explore the patterns of the spread of information and to identify extent to which social media correlates to the agenda of traditional media and vice versa. Results show that the application of computer-aided methods can efficiently identify the most important issues of public and media agenda, such as the global nature of pandemic, the response of the government as well as information about disease control measures. Findings illustrate core differences between traditional and social media and provide evidence that to a certain extent the public agenda can alter agendas of traditional media. This research shows the potential of using social media to conduct “infodemic” studies for the public health. The methodology created in research can be used to track information diffusion and to analyse near real-time content, allowing health authorities to respond to public concerns more quickly.
- 3.4. Other publications in conference proceedings (including local)