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Mixed Methods Social Network Analysis (Theories and Methodologies in Learning and Education) - 9780367174453

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9780367174453
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  • Product Details

    Author:
    Dominik E. Froehlich, Martin Rehm, Bart C. Rienties
    Format:
    Paperback
    Pages:
    292
    Publisher:
    Taylor & Francis (December 24, 2019)
    Language:
    English
    ISBN-13:
    9780367174453
    Weight:
    19.125oz
    Dimensions:
    6.125" x 9.1875"
    File:
    TAYLORFRANCIS-TayFran_260403050946149-20260403.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $68.99
    Case Pack:
    24
    As low as:
    $65.54
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    Routledge
  • Overview

    Mixed Methods Social Network Analysis brings together diverse perspectives from 42 international experts on how to design, implement, and evaluate mixed methods social network analysis (MMSNA). There is an increased recognition that social networks can be important catalysts for change and transformation.

    This edited book from leading experts in mixed methods and social network analysis describes how researchers can conceptualize, develop, mix, and intersect diverse approaches, concepts, and tools. In doing so, they can improve their understanding and insights into the complex change processes in social networks. Section 1 includes eight chapters that reflect on "Why should we do MMSNA?", providing a clear map of MMSNA research to date and why to consider MMSNA. In Section 2 the remaining 11 chapters are dedicated to the question "How do I do MMSNA?", illustrating how concentric circles, learning analytics, qualitative structured approaches, relational event modeling, and other approaches can empower researchers.

    This book shows that mixing qualitative and quantitative approaches to social network analysis can empower people to understand the complexities of change in networks and relations between people. It shows how mixed analysis can be applied to a wide range of data generated by diverse global communities: American school children, Belgian teachers, Dutch medical professionals, Finnish consultants, French school children, and Swedish right-wing social media users, amongst others. It will be of great interest to researchers and postgraduate students in education and social sciences and mixed methods scholars.