Dr Valentin Danchev

Department of Sociology
Dr Valentin Danchev



Valentin is a Lecturer in Computational Social Science in the Department of Sociology at the University of Essex. His research leverages large datasets and methods from computational social science, social data science, and network analysis to study diverse social phenomena such as transparency and reproducibility of scientific research, human mobility, global migration, inequality, and digital-health interventions. Valentin's background is interdisciplinary and has involved collaborations across sciences. He completed his DPhil in Development Studies at the University of Oxford where he studied global migration and network science, and was also affiliated with the networks research group at the Mathematical Institute. Prior to joining Essex in 2020, he held postdoctoral positions at the Stanford University School of Medicine and, before that, at the University of Chicago. He is a strong supporter of open and reproducible research practices. He has a special interest in designing data-sharing interventions and socio-technological infrastructures to incentivise open research and data-driven discovery at scale. As a social data science educator, Valentin strives to enable open, inclusive, and collaborative learning, and to bring ethics, computing, machine learning, causal inference, and data to bear on critical societal issues.


  • DPhil Development Studies University of Oxford, (2015)

  • MA Sociological Research University of Essex, (2010)


University of Essex

  • Lecturer, Department of Sociology, University of Essex (1/7/2020 - present)

Research and professional activities

Research interests

Social Data Science

Computational Social Science

Social Networks

Open and Reproducible Science

Data and Society

Human Mobility

Global Migration

Social Inequality

Digital Health Interventions

Open Data

Teaching and supervision

Current teaching responsibilities

  • Social Data Science: Code, Text and Networks (SC207)

  • Quantitative Research on Social Stratification: Inequalities from Cradle to Grave (SC208)

  • Models and Measurement in Quantitative Sociology (SC385)

  • Advanced Quantitative Analysis: Models for Cause and Effect (SC968)


Journal articles (5)

Danchev, V., Min, Y., Borghi, J., Baiocchi, M. and Ioannidis, JPA., (2021). Evaluation of Data Sharing After Implementation of the International Committee of Medical Journal Editors Data Sharing Statement Requirement.. Jama Network Open. 4 (1), e2033972-e2033972

Hardwicke, TE., Serghiou, S., Janiaud, P., Danchev, V., Crüwell, S., Goodman, SN. and Ioannidis, JPA., (2020). Calibrating the Scientific Ecosystem Through Meta-Research. Annual Review of Statistics and Its Application. 7 (1), 11-37

Janiaud, P., Axfors, C., van't Hooft, J., Saccilotto, R., Agarwal, A., Appenzeller-Herzog, C., Contopoulos-Ioannidis, DG., Danchev, V., Dirnagl, U., Ewald, H., Gartlehner, G., Goodman, SN., Haber, NA., Ioannidis, AD., Ioannidis, JPA., Lythgoe, MP., Ma, W., Macleod, M., Malički, M., Meerpohl, JJ., Min, Y., Moher, D., Nagavci, B., Naudet, F., Pauli-Magnus, C., O'Sullivan, JW., Riedel, N., Roth, JA., Sauermann, M., Schandelmaier, S., Schmitt, AM., Speich, B., Williamson, PR. and Hemkens, LG., (2020). The worldwide clinical trial research response to the COVID-19 pandemic - the first 100 days. F1000Research. 9, 1193-1193

Danchev, V., Rzhetsky, A. and Evans, JA., (2019). Centralized scientific communities are less likely to generate replicable results. eLife. 8

Danchev, V. and Porter, MA., (2018). Neither global nor local: Heterogeneous connectivity in spatial network structures of world migration. Social Networks. 53, 4-19



Colchester Campus

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