Dr Claudia Zucca

  • Research Assistant (MRC/CSO Social & Public Health Sciences Unit)


Claudia is a research assistant working in the Complexity Programme and the Relationships Programme at the MRC/CSO Social and Public Health Sciences Unit.

Previously, she worked as a research assistant in the department of social sciences for the Impact Acceleration Account funded project “Support Infrastructure and Impact Maintenance for Scientific Reproducibility Software”. She also was a research associate at the University of Exeter analysing the environmental organisations in the US with social network analysis and analysis of big data scraped from social networks such as Twitter. 

She holds a PhD in quantitative politics from the University of Exeter, achieved under the framework of the Marie Curie Industrial Doctorate program with the project VoteAdvice, where she completed a dissertation that looks at the formation of public opinion using a meta-theory based on a complex system perspective.  

She has a BA in International Relations and an MA in Organisation and Governance from the University of Bologna (Italy), an MSc in Political Communication Advocacy and Campaigning from Kingston University (London, UK), and an MA in Public Policy and Governance from LUISS Guido Carli University (Rome, Italy). She has also spent one year at the Central European University in Budapest learning social network analysis, network science and complexity approaches.

Research interests

Claudia is interested in the analysis of complex systems and in using this approach to develop interventions in health. Inside this framework, she looks at the normalisation of new processes and innovation among social actors and organisations and how people change opinion in reaction to innovation. For instance, how new approaches are received and implemented by health organisations and how new best practices of health behaviour are accepted by the population. She is also interested in understanding the relations that drive people’s behaviour in relation to health.

From a methodological perspective, she is interested in every method that can be used to explain complexity such as network analysis, network science approaches and system mapping. 

She also likes experimental methods, econometrics, and she is very open to the use of qualitative methods too.

She usually carries out her work in the R language, and she has experience of R package development.


Claudia has experience teaching network analysis (descriptive and inferential), data analysis in R and statistics.