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This approachable book introduces network research in R, walking
you through every step of doing social network analysis. Drawing
together research design, data collection and data analysis, it
explains the core concepts of network analysis in a non-technical
way. The book balances an easy to follow explanation of the
theoretical and statistical foundations underpinning network
analysis with practical guidance on key steps like data management,
preparation and visualisation. With clarity and expert insight, it:
* Discusses measures and techniques for analyzing social network
data, including digital media * Explains a range of statistical
models including QAP and ERGM, giving you the tools to approach
different types of networks * Offers digital resources like
practice datasets and worked examples that help you get to grips
with R software
Social Networks at Work provides the latest thinking, from
top-notch experts, on social networks as they apply to industrial
and organizational (I/O) psychology. Each chapter provides an
in-depth review along with discussions of future research and
managerial implications of the social network perspective.
Altogether, the volume illustrates the importance of adding a
social capital perspective to the traditional human capital focus
of I/O psychology. The volume is organized into two groups of
chapters: the first seven chapters focus on specific network
concepts (such as centrality, affect, negative ties, multiplexity,
cognition, and structural holes) applied across a variety of
topics. The remaining eight chapters focus on common I/O topics
(such as personality, creativity, turnover, careers,
person-environment fit, employment, teams, and leadership) and
examine each from a network perspective, applying a variety of
network concepts to the topic. This volume is suited for students
and academics interested in applying a social network perspective
to their work, as well as for practicing managers. Each topic area
provides a useful review and guide for future research, as well as
implications for managerial action.
Social network analysis has transformed the study of organizations
over the past 30 years. Rather than focus on individuals or teams,
network scholars view the organization as a nexus of relationships.
As its popularity increases, the scholarship is evolving in many
directions including new theory on network dynamics, multilevel
thinking, multiplex networks, digital networks, instrumental and
affective ties, and cross-cultural considerations, in addition to
advances in methods and measures, and new organizational
applications. This compendium of essays points the way to
contemporary issues in organizational social networks. Research in
the Sociology of Organizations is an established international,
peer-reviewed series that examines cutting edge theoretical,
methodological and research issues in organizational studies. The
series is especially concerned with specifying the unique
contributions of sociological theories and research techniques to
the analysis of organizations. In addition to publishing high
quality original research, each volume aims to foster debate about
the value of new theories and research to the growing international
community of organizational studies scholars. Each volume is
designed around carefully selected and interesting themes that aim
to facilitate the development of new research communities and
perspectives within the organizational studies field. All
contributions are peer reviewed to ensure high quality, and are
individually downloadable through your library website, enabling
wide distribution and easy access.
Social Networks at Work provides the latest thinking, from
top-notch experts, on social networks as they apply to industrial
and organizational (I/O) psychology. Each chapter provides an
in-depth review along with discussions of future research and
managerial implications of the social network perspective.
Altogether, the volume illustrates the importance of adding a
social capital perspective to the traditional human capital focus
of I/O psychology. The volume is organized into two groups of
chapters: the first seven chapters focus on specific network
concepts (such as centrality, affect, negative ties, multiplexity,
cognition, and structural holes) applied across a variety of
topics. The remaining eight chapters focus on common I/O topics
(such as personality, creativity, turnover, careers,
person-environment fit, employment, teams, and leadership) and
examine each from a network perspective, applying a variety of
network concepts to the topic. This volume is suited for students
and academics interested in applying a social network perspective
to their work, as well as for practicing managers. Each topic area
provides a useful review and guide for future research, as well as
implications for managerial action.
To better understand how structure, content and meaning are
interrelated, there is great potential in conceptualizing mixed
structure linkages, where social relations, events, actions and
text-based information intersect. This potential is all the more
salient in view of the large data flows and analytical tools that
researchers can draw on. However, the increasing availability of
tools and data seem to outpace theory development. In response to
these trends, this volume aims to advance theoretical understanding
of how structure, content and meaning are dynamically intertwined,
in both online and offline domains. We also explain the
methodological implications of such investigations. This volume
therefore responds to the need for in-depth analyses studying the
theoretical and methodological implications of the assumed unity of
network approaches at the intersections of structure, content and
meaning. With these analyses, we show promising approaches, provoke
debates in the field, and suggest potential future directions.
This approachable book introduces network research in R, walking
you through every step of doing social network analysis. Drawing
together research design, data collection and data analysis, it
explains the core concepts of network analysis in a non-technical
way. The book balances an easy to follow explanation of the
theoretical and statistical foundations underpinning network
analysis with practical guidance on key steps like data management,
preparation and visualisation. With clarity and expert insight, it:
* Discusses measures and techniques for analyzing social network
data, including digital media * Explains a range of statistical
models including QAP and ERGM, giving you the tools to approach
different types of networks * Offers digital resources like
practice datasets and worked examples that help you get to grips
with R software
Designed to walk beginners through core aspects of collecting,
visualizing, analyzing, and interpreting social network data, this
book will get you up-to-speed on the theory and skills you need to
conduct social network analysis. Using simple language and
equations, the authors provide expert, clear insight into every
step of the research process-including basic maths
principles-without making assumptions about what you know. With a
particular focus on NetDraw and UCINET, the book introduces
relevant software tools step-by-step in an easy to follow way. In
addition to the fundamentals of network analysis and the research
process, this Second Edition focuses on: Digital data and social
networks like Twitter Statistical models to use in SNA, like QAP
and ERGM The structure and centrality of networks Methods for
cohesive subgroups/community detection Supported by new chapter
exercises, a glossary, and a fully updated companion website, this
text is the perfect student-friendly introduction to social network
analysis.
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.
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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