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  3. Egocentric Network Analysis
  • Cited by 444
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    • Publisher:
      Cambridge University Press
      Publication date:
      27 February 2018
      15 March 2018
      ISBN:
      9781316443255
      9781107131439
      9781107579316
      DOI:
      https://doi.org/10.1017/9781316443255
      Dimensions:
      (228 x 152 mm)
      Weight & Pages:
      0.63kg, 366 Pages
      Dimensions:
      (228 x 152 mm)
      Weight & Pages:
      0.56kg, 366 Pages
      • Subjects:
      Social Theory, Research Methods in Politics, Research Methods in Sociology and Criminology, Research Methods In Sociology and Criminology, Politics and International Relations, Research Methods In Politics, Sociology
      Series:
      Structural Analysis in the Social Sciences (44)
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    Subjects:
    Social Theory, Research Methods in Politics, Research Methods in Sociology and Criminology, Research Methods In Sociology and Criminology, Politics and International Relations, Research Methods In Politics, Sociology
    Series:
    Structural Analysis in the Social Sciences (44)
    Information

    Book description

    Egocentric network analysis is used widely across the social sciences, especially in anthropology, political science, economics, and sociology, and is increasingly being employed in communications, informatics, and business and marketing studies. Egocentric network analysis requires a unique set of data collection and analysis skills that overlap only minimally with other network methodologies. However, until now there has been no single reference for conceptualizing, collecting, and analyzing egocentric social network data. This comprehensive guide to study design, data collection, and analysis brings together the state of knowledge with the most effective research tools to guide newcomers to this field. It is illustrated with many engaging examples and graphics and assumes no prior knowledge. Covering the entire research process in a logical sequence, from conceptualizing research questions to interpreting findings, this volume provides a solid foundation for researchers at any stage of their career to learn and apply ego network methods.

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