About the Method: Response Item Networks (ResIN)

Within Response Item Networks, nodes represent responses to survey questions, and a link between two response nodes means that both responses tend to be held simultaneously within the studied population (i.e. a positive correlation). The higher the correlation between two response nodes, the closer they are placed to one another. The main axis of the network then shows which responses cluster together and which do not, without presupposing clusters, social groups etc. For more information about the method, software tools or the researchers behind it, see the following links.

Website: www.resinmethod.net

Published

  • Carpentras, D., Lüders, A. & Quayle, M. (2022). Mapping the global opinion space to explain anti-vaccine attraction. Scientific Reports, 12, 6188. doi:10.1038/s41598-022-10069-3
  • Lüders, A., Carpentras, D., & Quayle, M. (2023). Attitude networks as intergroup realities: Using network-modelling to research attitude-identity relationships in polarized political contexts. British Journal of Social Psychology. doi:10.1111/bjso.12665
  • Carpentras, D., Lüders, A., & Quayle, M. (2024). Response Item Network (ResIN): A network-based approach to explore attitude systems. Humanities and Social Sciences Communications, 11(1), 1-14. doi:10.1057/s41599-024-03037-x
  • Chen, Y., Speer, A., De Bruin, B., Carpentras, D., & Warncke, P. (2025). A “broken egg” of US political beliefs: Using response-item networks (ResIN) to measure ideological polarization. Network Science, 13, e20. doi:10.1017/nws.2025.10016
  • Warncke, P., Chen, Y., Speer, A., de Bruin, B., Lüders, A., & Carpentras, D. (2026). ResIN: A new method to analyze socio-political attitude systems. In Computational Social Science of Social Cohesion and Polarization (pp. 105-129). Springer. doi:10.1007/978-3-032-01373-6_5

Preprints and reports

  • Warncke, P., Carpentras, D., Lüders, A., & Quayle, M. (2026). Introducing ResIN: An applied tutorial to the Response-Item-Networks package for R. doi:10.7910/DVN/WQLSIP
  • Carpentras, D., Lüders, A., Warncke, P., & Morselli, D. (2026). Belief Network Theory: A conceptual framework for studying complex attitude-identity systems. doi:10.13140/RG.2.2.35745.88169
  • Carpentras, D. (2021). Bridging networks with linear spaces to study attitudes and political polarization [ResIN on Twitter data]. Link
  • Carpentras, D. (2019). A method for estimating distance in opinion dynamics models using surveys data [“proto-ResIN”]. doi:10.13140/RG.2.2.29644.77449
Made by: Bart de Bruin
Label scale
Min Neutral Max
  1. 2024, American National Election Studies (2026). ANES 2024 Time Series Study Full Release [Data set]. May 19, 2026 version. Stanford University and the University of Michigan. electionstudies.org
  2. 2020, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org
  3. 2016, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org
  4. 2012, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org
  5. 2008, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org
  6. 2004, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org
  7. 2000, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org
  8. 1996, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org
  9. 1992, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org
  10. 1988, American National Election Studies (2022). ANES Time Series Cumulative Data File, 1948-2020 [Data set]. September 16, 2022 version. Stanford University and the University of Michigan. electionstudies.org