This chapter has the exploratory goal of understanding the attitudes and perceptions of 'verified' Twitter (VA) accounts about the COVID-19 vaccine campaign. Identifying their sentiment and opinion about it could therefore be crucial to the success of vaccination. A content analysis of tweets from the period December 24, 2020 to March 23, 2021 about the vaccine campaign in Italy was conducted to understand the semantic strategies used by VAs based on their orientation toward the vaccine, whether pro, anti, or neutral, and their possible motivations. Topic modeling allowed the authors to detect five prevalent themes and their associated words. A sentiment analysis and opinion analysis were performed on a smaller sample of tweets. The results suggest that 'authoritative' opinion about the vaccine has been very fragmented and not entirely positive, as expected. This could prove to be a critical issue in getting the vaccine positively accepted by the public.
TopIntroduction
On December 27 in Italy was held the Vaccine day, the “symbolic” beginning of the vaccination campaign against COVID-19. It is a historic event because it involves at the same time almost the entire world population. Although the vaccine represents evidence of worldwide cooperation and a great step forward by the scientific community, it has not gained unanimous support from the population. Vaccination against COVID-19 is not free from a significant feeling of diffidence. Digital media and social platforms have been the privileged channels for the unfiltered circulation of no-vax feelings. Negative perceptions towards the vaccine are not new, and researchers are constantly studying evidences on ‘no-vax’ or ‘vaccine-hesitancy’ attitudes. However, widespread distrust of the Coronavirus vaccine campaign has reached very high levels, and this risks compromising or delaying population immunity. Social media represent the ideal environment to study this phenomenon.We know, however, that in the formation of opinions, attitudes and beliefs is very relevant the mediation of actors or groups as credible sources. Studying directly the communication of these sources can better highlight the mechanisms behind the vaccine social narrative. Lack of trust in the health care system appears to be among the triggers for opposition to vaccines (Kata, 2010). In fact, in recent times, a new model of health care has emerged, in which power has shifted from physicians to patients and the validity of science is constantly questioned (Kata, 2012). The Internet has facilitated this process of democratization of knowledge by making the process of discerning authoritative sources complex. About 80% of Internet users search for health information online and about 16% of them search for online news about vaccinations, bypassing direct contact with health care professionals. The communication that circulates online about the Coronavirus vaccination campaign could decisively affect its success. This contribution aims to understand the attitude and perception of actors (public or private organizations and individuals) very popular and with a large following on the social platform of Twitter. They inspire people's trust likely to influence their beliefs and perceptions towards the vaccine. So identifying their sentiment and opinion about it could be crucial for the success of the vaccination campaign.
A text analysis of the tweets of 'verified' user accounts (VA ('Verified Account') henceforth) on the vaccine campaign in Italy was carried out to understand the semantic strategies used by VAs according to their orientation towards the vaccine, whether in favor, against or neutral, and their possible motivations. Understanding the communication strategies of the very popular actors on the vaccine could be useful to identify at an early stage the trends of public opinion and the most frequently circulating issues. The paper is divided into 4 sections: the first one introduces the theoretical background, describing the evolution of opinion leader in the digital environments and its importance in the construction of attitudes. There will also be room for a brief digression on the typology of attitudes towards the vaccine identified in the literature. The second section describes the methods used, i.e., tweet collection and data analysis tools, and the methods that involved in-depth investigation of a small sample of tweets. The third gives an overview of the results and outputs of the sentiment and opinion analysis. The last part is devoted to the concluding discussion of the results and possible future research.