Craft, Curiosity, and Knowledge: Duncan Watts in Conversation with Philipp Brandt
DOI:
https://doi.org/10.60923/issn.1971-8853/24939Keywords:
Social networks, Research design, Knowledge accumulation, Scientific practiceAbstract
Duncan Watts’ work has helped define how we study social relations, collective dynamics, and digital platforms. It ranges from articles combining formal modeling and empirical discoveries to widely read books. He has moved between disciplines and problems, shaping the fields of network science and computational social science along the way. In this conversation with Philipp Brandt, he retraces his steps and maps out an integrative framework that flips the research design process to start with problems and produce generalizable knowledge.References
Alsobay, M., Rand, D.G., Watts, D.J., & Almaatouq, A. (2026). Integrative Experiments Identify How Punishment Affects Welfare in Public Goods Games. Science, 392(6794). https://doi.org/10.1126/science.aeb5280
Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades. Journal of Political Economy, 100(5), 992–1026. https://doi.org/10.1086/261849
Cohen, J. (1994). The earth is round. American psychologist, 49(12), 997–1003.
Glaser, B.G., & Strauss, A.L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Chicago: Aldine.
Granovetter, M. (1978). Threshold Models of Collective Behavior. American Journal of Sociology, 83(6), 1420–1443. https://doi.org/10.1086/226707
Hofman, J.M., Sharma, A., & Watts, D.J. (2017). Prediction and Explanation in Social Systems. Science, 355(6324), 486–488. https://doi.org/10.1126/science.aal3856
Hofman, J.M., Watts, D.J., Athey, S., Garip, F., Griffiths, T.L., Kleinberg, J., … Vazire, S. (2021). Integrating Explanation and Prediction in Computational Social Science. Nature, 595(7866), 181–188. https://doi.org/10.1038/s41586-021-03659-0
Newman, M.E.J., Moore, C., & Watts, D.J. (2000). Mean-field Solution of the Small-world Network Model. Physical Review Letters, 84(14), 3201–3204. https://doi.org/10.1103/PhysRevLett.84.3201
Newman, M.E.J., & Watts, D.J. (1999a). Renormalization Group Analysis of the Small-world Network Model. Physics Letters A, 263(4–6), 341–346. https://doi.org/10.1016/S0375-9601(99)00757-4
Newman, M.E.J., & Watts, D.J. (1999b). Scaling and Percolation in the Small-world Network Model. Physical Review E, 60(6), 7332–7342. https://doi.org/10.1103/PhysRevE.60.7332
Watts, D.J. (1999). Networks, Dynamics, and the Small-world Phenomenon. American Journal of Sociology, 105(2), 493–527. https://doi.org/10.1086/210318
Watts, D.J. (2004). Six Degrees: The Science of a Connected Age. New York: W.W. Norton & Company.
Watts, D.J. (2022). Five Feet at a Time. Sociologica, 16(1), 59–66. https://doi.org/10.6092/issn.1971-8853/14863
Watts, D.J., & Dodds, P.S. (2009). Threshold Models of Social Influence. In P. Hedström & P. Bearman (Eds.), The Oxford Handbook of Analytical Sociology (pp. 475–497). Oxford, UK: Oxford University Press.
Watts, D.J., & Strogatz, S.H. (1998). Collective Dynamics of “Small-World” Networks. Nature, 393, 440–442. https://doi.org/10.1038/30918
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Philipp Brandt, Duncan J. Watts
This work is licensed under a Creative Commons Attribution 4.0 International License.
