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A webometric approach to policy analysis and management using exponential random graph models

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Abstract

Many studies have examined citizen participation in policymaking and its delivery mechanisms through social media tools such as Facebook, Twitter, and YouTube, but few have explored empirical strategies to investigate the nature of online citizen participation in the field of policy analysis and management. The webometric approach is a quantitative tool for capturing network-based intercommunication derived from the Web 2.0 sphere as user-generated content by using diverse methods in informetrics. By applying this approach to examine citizen participation on social media, this study introduces an empirical strategy for collecting data on social media tools used by governments and identifies patterns of citizens’ e-participation and relationships between citizens, governments, and various organizations involved in policymaking processes through social media. The results based on the 311 service platforms of New York City and San Francisco suggest that the webometric approach can not only extract government agencies’ communication behaviors toward others on social media but also capture the overall network structure, the pattern of interactions between participants, and network properties of participants.

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Authors and Affiliations

  1. Department of Public Administration, University of North Texas, Denton, TX, USA

    Kyujin Jung & Wei-Ning Wu

  2. Department of Communication, Georgia State University, Atlanta, GA, USA

    Se Jung Park

  3. Department of Media and Communication, YeungNam University, Gyeongsan, South Korea

    Han Woo Park

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  1. Kyujin Jung
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Correspondence to Han Woo Park.

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Jung, K., Park, S.J., Wu, WN. et al. A webometric approach to policy analysis and management using exponential random graph models. Qual Quant 49, 581–598 (2015). https://doi.org/10.1007/s11135-014-0010-2

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