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  • SAGE Publications  (2)
  • Sociology  (2)
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  • SAGE Publications  (2)
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  • 1
    Online Resource
    Online Resource
    SAGE Publications ; 2021
    In:  Sociological Methods & Research Vol. 50, No. 4 ( 2021-11), p. 1515-1551
    In: Sociological Methods & Research, SAGE Publications, Vol. 50, No. 4 ( 2021-11), p. 1515-1551
    Abstract: Given the questionnaire design and the nature of the problem, partially ordered data that are neither completely ordered nor completely unordered are frequently encountered in social, behavioral, and medical studies. However, early developments in partially ordered data analysis are very limited and restricted only to cross-sectional data. In this study, we propose a Bayesian two-level regression model for analyzing repeated partially ordered responses in longitudinal data. The first-level model is defined for partially ordered observations of interest that are taken at each time point nested within individuals, while the second-level model is defined for individuals to assess the effects of their characteristics on the first-level model. A full Bayesian approach with the Markov chain Monte Carlo algorithm is developed for statistical inference. Simulation studies demonstrate the satisfactory performance of the developed methodology. The methodology is then applied to a longitudinal study on adolescent smoking behavior.
    Type of Medium: Online Resource
    ISSN: 0049-1241 , 1552-8294
    RVK:
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2021
    detail.hit.zdb_id: 2002146-X
    detail.hit.zdb_id: 121808-6
    SSG: 3,4
    Location Call Number Limitation Availability
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  • 2
    In: New Media & Society, SAGE Publications, Vol. 20, No. 9 ( 2018-09), p. 3161-3182
    Abstract: Building on studies of the hybrid media system and attention economy, we develop the concept of amplification to explore how the activities of social media–based publics may enlarge the attention paid to a given person or message. We apply the concept to the 2016 US election, asking who constituted Donald Trump’s enormous Twitter following and how that following contributed to his success at attracting attention, including from the mainstream press. Using spectral clustering based on social network similarity, we identify key publics that constituted Trump’s Twitter following and demonstrate how particular publics amplified his social media presence in different ways. Our discussion raises questions about how algorithms “read” metrics to guide content on social media platforms, how journalists draw on social media metrics in their determinations of news value and worthiness, and how the process of amplification relates to possibilities of citizen action through digital communication.
    Type of Medium: Online Resource
    ISSN: 1461-4448 , 1461-7315
    RVK:
    RVK:
    RVK:
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
    detail.hit.zdb_id: 1476527-5
    detail.hit.zdb_id: 2684519-2
    detail.hit.zdb_id: 2016312-5
    detail.hit.zdb_id: 2686704-7
    SSG: 24,1
    SSG: 3,4
    SSG: 3,5
    Location Call Number Limitation Availability
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