Changing Images? Italian Twitter Discourse on China and the United States during the First Wave of COVID-19

ABSTRACT

Although public diplomacy and its influence on foreign public opinion have been central themes in recent research, the latter often lacks methodological diversity and does not consider how states create competing images. Our study offers a framework for understanding Italian public opinion using a triangulation approach that combines traditional public opinion surveys with advanced text analysis of social media content. We compare the representation of China and the United States in the Italian Twitter community during the first wave of the COVID-19 pandemic. Our analysis shows that Italians who perceived China as a viable alternative to Western governments in public opinion surveys did so because they distrusted Western leaders and institutions.

KEYWORDS:

• COVID-19
• China
• United States
• public opinion
• topic models

Acknowledgements

The authors are grateful to the two anonymous reviewers for their feedback and to the journal’s editorial team for their support. They also would like to thank Jonathan Hassid, Iowa State University, for their comments at the APSA Conference 2021. The authors should be considered equally responsible for the overall arguments presented in the article. Adhering to Italian academic requirements and conventions, the attribution of authorship is delineated as follows: C.R. Combei and F. Maracchione collaborated on “Research design” and “Methods”; C.R. Combei authored “Data” and “Lexicon-based sentiment and emotion analyses”; F. Maracchione authored “STM findings” and “Discussion”; G. Sciorati authored the introduction and “Foreign public opinion and international relations”. All three authors contributed to the concluding section.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data supporting the results of this study was scraped from Twitter and is available upon request.

Funding statement

This work is funded by the Economic and Social Research Council (ESRC) and PON Ricerca e Innovazione 2014-2020.

Notes

1 All subsequent mentions of the R software refer to the 2021 release.

2 Alessandro Di Battista was amongst of the most popular leaders of the Five Star Movements (5SM) and a member of the House of Deputies between 2013 and 2018. He was known for his critical stance on the 5SM’s agreements with established political parties and his support for direct democracy inside the 5SM. This led him to leave the Movement in 2021 after the party’s leadership decided to join the government led by Mario Draghi.

3 In the US case, trust seems to be the most prevalent emotion. However, the data show that tweets conveying the opposite emotion (for example, “mistrust” or “scepticism”) were also labelled as “trust”. This mislabelling highlights one of the major limitations of lexicon-based emotion analysis, which only considers the lexical-semantic level of a word, and thus the need to triangulate findings.

4 See the Appendix – available upon request from the authors – for a detailed summary of each topic, including sentiment, context and examples.

Additional information

Notes on contributors

Frank Maracchione

Frank Maracchione is a PhD Candidate at the University of Sheffield, Sheffield, United Kingdom.

Giulia Sciorati

Giulia Sciorati was a Postdoctoral Research Fellow at the University of Trento, Trento, Italy, and is now a Fellow in the Department of International Relations at the London School of Economics and Political Science, London, United Kingdom. Email: [email protected]; Twitter/X: @GiuliaSciorati

Claudia Roberta Combei

Claudia Roberta Combei is an Assistant Professor at the University of Pavia, Pavia, Italy. Email: [email protected]; Twitter/X: @RobertaCombei