Humans are a social species, being influenced by the thoughts and behaviours of people in their networks. Characterising these networks, and getting data on them, is difficult.
March 18, 2021
Humans are uniquely social, being influenced by the ideas and behaviours of others even to their own detriment. Thus, people’s social networks are essential in their behaviour. Yet, collecting and analysing such network is not trivial.
Using specifically designed software to capture people’s personal network during an online survey, I have managed to collect data on large personal networks on a representative sample of Dutch women via the LISS panel. Related work:
Stulp, G. (2023). Describing the Dutch Social Networks and Fertility Study and how to process it. Demographic Research 49(19), 493-512. https://www.demographic-research.org/articles/volume/49/19 Download
Stulp, G. (2023). FertNet: Process data from the social networks and fertility survey. https://CRAN.R-project.org/package=FertNet.
Stulp, G. (2021). Collecting large personal networks in a representative sample of Dutch women. Social Networks 64: 63-71. https://doi.org/10.1016/j.socnet.2020.07.012.
Buijs, V. L., & Stulp, G. (2022). Friends, family, and family friends: Predicting friendships of Dutch women. Social Networks, 70, 25-35. https://doi.org/10.1016/j.socnet.2021.10.008. Download
Stadel, M., & Stulp, G. (2022). Balancing bias and burden in personal network studies. Social Networks, 70, 16-24. https://doi.org/10.1016/j.socnet.2021.10.007. Download
Stulp, G & Barrett, L. (2021). Do data from large personal networks support cultural evolutionary ideas about kin and fertility? Social Sciences 10(5):177. https://doi.org/10.3390/socsci10050177. Download
Stulp, G., Top, L., Xu, X., & Sivak, E. (2023). A data-driven approach shows that individuals’ characteristics are more important than their networks in predicting fertility preferences. Royal Society Open Science 10(12), 230988. https://doi.org/10.1098/rsos.230988 Download
Both Anna Langener and Marie Stadel work on how to best capture and analyse the social environment (including through personal network data collection, Experience Sampling Method data, and Digital Phenotyping data). Related work:
Langener, A. M., Stulp, G., Jacobson, N. C., Costanzo, A., Jagesar, R. R., Kas, M. J., & Bringmann, L. F. (2024). It’s All About Timing: Exploring Different Temporal Resolutions for Analyzing Digital-Phenotyping Data. Advances in Methods and Practices in Psychological Science, 7(1), 25152459231202677. https://doi.org/10.1177/25152459231202677 Download
Langener, A. M., Bringmann, L. F., Kas, M. J., & Stulp, G. (2024). Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks. Administration and Policy in Mental Health and Mental Health Services Research. https://doi.org/10.1007/s10488-023-01328-0 Download
Stadel, M., Stulp, G., Langener, A. M., Elmer, T., van Duijn, M. A. J., & Bringmann, L. F. (2023). Feedback About a Person’s Social Context - Personal Networks and Daily Social Interactions. Administration and Policy in Mental Health and Mental Health Services Research. https://doi.org/10.1007/s10488-023-01293-8 Download