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Uncovering the Strategies and Dynamics of Research Fields Using Network Science: Structural Evidence from a Decade of Privacy Research

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Abstract

Objective

This study aims to better understand the dynamics, organisation and collaboration strategies of a research community through social network analysis. While network is particularly adapted to handling the complexity of social interactions between groups, it is currently underused in many research fields. The topology of the social graph and collaboration strategies is rarely investigated or discussed despite its potential usefulness in understanding group dynamics. The author-strategic diagram, based on social network analysis metrics, is proposed and discussed.

Methods

Our analysis considers 10 years of co-authored research publications on privacy. First, we explore the dynamics of the community by analysing the incoming, remaining and departing authors, and the authors’ publishing lifetimes. Second, we focus on the dynamics using social network analysis metrics: distance, modularity, node centralities, local clustering coefficient, assortativity.

Results

Despite the multi-disciplinary nature of privacy research, collaborations exhibit cohesion and a small-world nature. However, the research community is hierarchical, the domain being structured around a few leaders and sub-leaders performing bridging roles between sub-communities. Authors collaborate with others in a similar position in the network except for the leaders, who collaborate a lot, but not with each other. Our author-strategic diagram shows the coexistence of divergent collaboration strategies within a single community related to multiple visions of social capital. Transition phases seem to be present; these could indicate future leaders of the community.

Conclusion

Our results highlight the disparity within the research community and the differing connection types that leaders and other researchers have. Our results show the usefulness of network science in understanding a research field’s community and its dynamics. Comparable analyses of other research communities could help to uncover similar patterns and to tie micro and macro theories together as we show for the theory of social capital.

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Authors and Affiliations

  1. PSB: Paris School of Business, 59 rue Nationale, Paris, France

    Charles Perez & Karina Sokolova

  2. Strategy and Management, IPAG Business School, 184 Boulevard Saint Germain, 75006, Paris, France

    Vincent Dutot

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  1. Charles Perez
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  2. Karina Sokolova
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Correspondence to Charles Perez.

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Perez, C., Sokolova, K. & Dutot, V. Uncovering the Strategies and Dynamics of Research Fields Using Network Science: Structural Evidence from a Decade of Privacy Research. Rev Socionetwork Strat 16, 573–597 (2022). https://doi.org/10.1007/s12626-022-00111-1

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