Communicating COVID-19 on Social Media: The Effects of the Spiral of Silence

Abstract

In this paper, the Spiral of Silence theory (SOS) in the study of mass communications is applied to examine the trends and mechanisms of public opinion in Social Media (SM), using the popular topic of the COVID-19 pandemic. The study includes a secondary analysis of the data on pandemic information consumption obtained through four mass surveys conducted in Armenia. In the period from July 1 to August 30, 2020, we also surveyed Armenian Facebook users by means of Google forms during the highest outbreak of the pandemic in Armenia. In particular, the study demonstrates that although the majority of people are well informed about both public conduct requirements and the sanctions for misconduct during the pandemic, they do not follow the rules but hide their real opinion, preferring to openly agree with the official position while silently breaking the rules (that is, they keep their silence). We have found a correlation between the opinion environment of “friends” and other Facebook users, and a willingness to express their own opinion. Due to the predominance of the self-presentation mode as a communication strategy on Facebook, there is a trend among Armenian users not to risk their reputation, and avoid possible critics by keeping silence, if the discussion goes against their opinion. The findings of the study might be helpful both for the further development of communication theories and its application to the conditions of new pandemic reality, and for a better understanding of communicative behavior mechanisms in SM.

An Empirical Study on the Causes of College Students' Participation in Internet Public Opinion and Its Countermeasures—Based on Data from Colleges and Universities in Harbin

“…[12]Coombs believes that the development of network public opinion can be divided into four stages. [13] The Opinion delayed forwarding immune Model (OD-SFI) was constructed by combining the forwarding volume, homogeneity and heterogeneity index of public opinion information in social networks to simulate the impact of user opinions on the communication efficiency of public opinion, and the model was fitted and sensitivity analyzed by combining the actual data. Scholar Noelle Neumann.…”