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Capturing the Social Life of a Person by Integrating Experience-Sampling Methodology and Personal-Social-Network Assessments
The daily social life of a person can be captured with different methodologies. Two methods that are especially promising are personal-social-network (PSN) data collection and experience-sampling methodology (ESM). Whereas PSN data collections ask participants to provide information on their social...
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Published in: | Advances in methods and practices in psychological science 2024-04, Vol.7 (2) |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The daily social life of a person can be captured with different methodologies. Two methods that are especially promising are personal-social-network (PSN) data collection and experience-sampling methodology (ESM). Whereas PSN data collections ask participants to provide information on their social relationships and broader social environment, ESM studies collect intensive longitudinal data on social interactions in daily life using multiple short surveys per day. In combination, the two methods enable detailed insights into someone’s social life, including information on interactions with specific interaction partners from the personal network. Despite many potential uses of such data integration, there are few studies to date using the two methods in conjunction. This is likely due to their complexity and lack of software that allows capturing the full social life of someone while keeping the burden for participants and researchers sufficiently low. In this article, we report on the development of methodology and software for an ESM/PSN integration within the established ESM tool m-Path. We describe results of a first study using the developed tool that illustrate the feasibility of the proposed method combination and show that participants consider the assessments insightful. We further outline study-design choices and ethical considerations when combining the two methodologies. We hope to encourage applications of the presented methods in research and practice across different fields. |
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ISSN: | 2515-2459 2515-2467 |
DOI: | 10.1177/25152459241244745 |