Network Analysis Literacy
Network Analysis Literacy

Author: Katharina A. Zweig

Publisher: Springer Science & Business Media

Published: 2016-10-26

Total Pages: 546

ISBN-13: 3709107415

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This book presents a perspective of network analysis as a tool to find and quantify significant structures in the interaction patterns between different types of entities. Moreover, network analysis provides the basic means to relate these structures to properties of the entities. It has proven itself to be useful for the analysis of biological and social networks, but also for networks describing complex systems in economy, psychology, geography, and various other fields. Today, network analysis packages in the open-source platform R and other open-source software projects enable scientists from all fields to quickly apply network analytic methods to their data sets. Altogether, these applications offer such a wealth of network analytic methods that it can be overwhelming for someone just entering this field. This book provides a road map through this jungle of network analytic methods, offers advice on how to pick the best method for a given network analytic project, and how to avoid common pitfalls. It introduces the methods which are most often used to analyze complex networks, e.g., different global network measures, types of random graph models, centrality indices, and networks motifs. In addition to introducing these methods, the central focus is on network analysis literacy – the competence to decide when to use which of these methods for which type of question. Furthermore, the book intends to increase the reader's competence to read original literature on network analysis by providing a glossary and intensive translation of formal notation and mathematical symbols in everyday speech. Different aspects of network analysis literacy – understanding formal definitions, programming tasks, or the analysis of structural measures and their interpretation – are deepened in various exercises with provided solutions. This text is an excellent, if not the best starting point for all scientists who want to harness the power of network analysis for their field of expertise.

Data Analysis, Interpretation, and Theory in Literacy Studies Research
Data Analysis, Interpretation, and Theory in Literacy Studies Research

Author: Michele Knobel

Publisher: Myers Education Press

Published: 2020-04-17

Total Pages: 236

ISBN-13: 1975502159

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Novice and early career researchers often have difficulty with understanding how theory, data analysis and interpretation of findings “hang together” in a well-designed and theorized qualitative research investigation and with learning how to draw on such understanding to conduct rigorous data analysis and interpretation of their analytic results. Data Analysis, Interpretation, and Theory in Literacy Studies Research demonstrates how to design, conduct and analyze a well put together qualitative research project. Using their own successful studies, chapter authors spell out a problem area, research question, and theoretical framing, carefully explaining their choices and decisions. They then show in detail how they analyzed their data, and why they took this approach. Finally, they demonstrate how they interpreted the results of their analysis, to make them meaningful in research terms. Approaches include interactional sociolinguistics, microethnographic discourse analysis, multimodal analysis, iterative coding, conversation analysis, and multimediated discourse analysis, among others. This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels. Perfect for courses such as: Literacy Research Seminar | Introduction to Qualitative Research | Advanced Research Methods | Studying New Literacies and Media | Research Perspectives in Literacy | Discourse Analysis | Advanced Qualitative Data Analysis | Sociolinguistic Analysis | Classroom Language Research

A First Course in Network Science
A First Course in Network Science

Author: Filippo Menczer

Publisher: Cambridge University Press

Published: 2020-01-30

Total Pages: 275

ISBN-13: 1108579612

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Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.

Network Science In Education
Network Science In Education

Author: Catherine B. Cramer

Publisher: Springer

Published: 2018-10-22

Total Pages: 205

ISBN-13: 3319772376

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Around the globe, there is an increasingly urgent need to provide opportunities for learners to embrace complexity; to develop the many skills and habits of mind that are relevant to today's complex and interconnected world; and to make learning more connected to our rapidly changing workplace and society. This presents an opportunity to (1) leverage new paradigms for understanding the structure and function of teaching and learning communities, and (2) to promote new approaches to developing methods, curricular materials, and resources. Network science - the study of connectivity - can play an important role in these activities, both as an important subject in teaching and learning and as a way to develop interconnected curricula. Since 2010, an international community of network science researchers and educators has come together to raise the global level of network literacy by applying ideas from network science to teaching and learning. Network Science in Education - which refers to both this community and to its activities - has evolved in response to the escalating activity in the field of network science and the need for people to be able to access the field through education channels. Network Science In Education: Transformational Approaches in Teaching and Learning appeals to both instructors and professionals, while offering case studies from a wide variety of activities that have been developed around the globe: the creation of entirely new courses and degree programs; tools for K-20 learners, teachers, and the general public; and in-depth analysis of selected programs. As network-based pedagogy and the community of practice continues to grow, we hope that the book's readers will join this vibrant network education community to build on these nascent ideas and help deepen the understanding of networks for all learners.

Statistical and Machine Learning Approaches for Network Analysis
Statistical and Machine Learning Approaches for Network Analysis

Author: Matthias Dehmer

Publisher: John Wiley & Sons

Published: 2012-06-26

Total Pages: 269

ISBN-13: 111834698X

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Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.

Social Network Theory and Educational Change
Social Network Theory and Educational Change

Author: Alan J. Daly

Publisher: Harvard Education Press

Published: 2010-12-01

Total Pages: 514

ISBN-13: 1612503764

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Social Network Theory and Educational Change offers a provocative and fascinating exploration of how social networks in schools can impede or facilitate the work of education reform. Drawing on the work of leading scholars, the book comprises a series of studies examining networks among teachers and school leaders, contrasting formal and informal organizational structures, and exploring the mechanisms by which ideas, information, and influence flow from person to person and group to group. The case studies provided in the book reflect a rich variety of approaches and methodologies, showcasing the range and power of this dynamic new mode of analysis. An introductory chapter places social network theory in context and explains the basic tools and concepts, while a concluding chapter points toward new directions in the field. Taken together, they make a powerful statement: that the success or failure of education reform ultimately is not solely the result of technical plans and blueprints, but of the relational ties that support or constrain the pace, depth, and direction of change. This unique volume provides an invaluable introduction to an emerging and increasingly important field of education research.

Social Structure and Network Analysis
Social Structure and Network Analysis

Author: Peter V. Marsden

Publisher: SAGE Publications, Incorporated

Published: 1982-11

Total Pages: 328

ISBN-13:

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Network analysis is being increasingly looked to as a means of understanding social structure. It can shed light on how individual actions create social structure, how social structure constrains the individual, and how attitudes and behaviour are determined by social structure. Articles by leading proponents of network analysis and structuralism examine how these methodological techniques and this theoretical approach can be applied to a variety of social phenomena. Written by some of the leading proponents of network analysis, this book will be welcomed by professionals in sociology and their students.

Actor-Network Theory in Education
Actor-Network Theory in Education

Author: Tara Fenwick

Publisher: Routledge

Published: 2010-07-02

Total Pages: 200

ISBN-13: 1136952888

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Actor-network theory (ANT) has enjoyed wide uptake in the social sciences in the past three decades, particularly in science and technology studies, and is increasingly attracting the attention of educational researchers. Across these diverse environments and uptakes, the authors trace how learning and practice - as assemblages of activity, actors and spaces - emerge, show what scales are at play, and demonstrate what this means for educational possibilities.

Social Network Analysis
Social Network Analysis

Author: John Scott

Publisher: SAGE

Published: 2017-02-16

Total Pages: 249

ISBN-13: 152641225X

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Incorporating the most important and cutting-edge developments in the field, this bestselling text introduces newcomers to the key theories and techniques of social network analysis and guides more experienced analysts in their own research. New to This Edition: A chapter on data collection, covering a crucial phase of the research process Fully updated examples reiterate the continued importance of social network analysis in an increasingly interconnected world Detailed ‘Further Reading’ sections help you explore the wider literature Practical exercises including real-world examples of social networks enable you to apply your learning Expanded and brought right up-to-date, this classic text remains the indispensable guide to social network analysis for students, lecturers and researchers throughout the social sciences.

Social network analysis
Social network analysis

Author: John Scott

Publisher:

Published: 2017

Total Pages: 234

ISBN-13: 9781529716597

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Incorporating the most important and cutting-edge developments in the field, this bestselling text introduces newcomers to the key theories and techniques of social network analysis and guides more experienced analysts in their own research. New to This Edition: • A chapter on data collection, covering a crucial phase of the research process • Fully updated examples reiterate the continued importance of social network analysis in an increasingly interconnected world • Detailed 'Further Reading'sections help you explore the wider literature • Practical exercises including real-world examples of social networks enable you to apply your learning Expanded and brought right up-to-date, this classic text remains the indispensable guide to social network analysis for students, lecturers and researchers throughout the social sciences.