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How Social Networks Influence Human Behavior: An Integrated Latent Space Approach for Differential Social Influence

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Abstract

How social networks influence human behavior has been an interesting topic in applied research. Existing methods often utilized scale-level behavioral data (e.g., total number of positive responses) to estimate the influence of a social network on human behavior. This study proposes a novel approach to studying social influence that utilizes item-level behavioral measures. Under the latent space modeling framework, we integrate the two latent spaces for respondents’ social network data and item-level behavior measures into a single space we call ‘interaction map’. The interaction map visualizes the association between the latent homophily among respondents and their item-level behaviors, revealing differential social influence effects across item-level behaviors. We also measure overall social influence by assessing the impact of the interaction map. We evaluate the properties of the proposed approach via extensive simulation studies and demonstrate the proposed approach with a real data in the context of studying how students’ friendship network influences their participation in school activities.

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Notes

  1. School 36 showed the lowest percentage of students receiving free or reduced lunch. Since School 36 was already selected, we chose School 44, the next one.

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Acknowledgements

We thank the editor, associate editor, and reviewers for their constructive com- ments. This work was supported by the National Research Foundation of Korea [Grant Number NRF 2020R1A2C1A01009881 and RS-2023-00217705; Basic Science Research Program awarded to IHJ] and the Yonsei University Research Grant of 2022 [Grant Number 2022-22-0439 awarded to JAP].

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  1. Department of Applied Statistics, Seoul, Republic of Korea

    Jina Park & Ick Hoon Jin

  2. Department of Statistics and Data Science, Yonsei University, Seoul,  03722, Republic of Korea

    Jina Park & Ick Hoon Jin

  3. School of Education and Information Studies, University of California, Los Angeles, USA

    Minjeong Jeon

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  1. Jina Park
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Park, J., Jin, I.H. & Jeon, M. How Social Networks Influence Human Behavior: An Integrated Latent Space Approach for Differential Social Influence. Psychometrika 88, 1529–1555 (2023). https://doi.org/10.1007/s11336-023-09934-5

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