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E-grāmata: Analyzing Social Media Networks with NodeXL: Insights from a Connected World

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(Department of Information Technology, Brigham Young University, Provo, Utah), , (Department of Computer Science and Founding Director of the HCI Lab, University of Maryland), (Chief Social Scientist, Connected Action Consulting Group;)
  • Formāts: 248 pages
  • Izdošanas datums: 08-May-2019
  • Izdevniecība: Morgan Kaufmann Publishers In
  • Valoda: eng
  • ISBN-13: 9780128177570
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  • Formāts: 248 pages
  • Izdošanas datums: 08-May-2019
  • Izdevniecība: Morgan Kaufmann Publishers In
  • Valoda: eng
  • ISBN-13: 9780128177570
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Analyzing Social Media Networks with NodeXL: Insights from a Connected World, Second Edition, provides readers with a thorough, practical and updated guide to NodeXL, the open-source social network analysis (SNA) plug-in for use with Excel. The book analyzes social media, provides a NodeXL tutorial, and presents network analysis case studies, all of which are revised to reflect the latest developments. Sections cover history and concepts, mapping and modeling, the detailed operation of NodeXL, and case studies, including e-mail, Twitter, Facebook, Flickr and YouTube. In addition, there are descriptions of each system and types of analysis for identifying people, documents, groups and events.

This book is perfect for use as a course text in social network analysis or as a guide for practicing NodeXL users.

  • Walks users through NodeXL while also explaining the theory and development behind each step
  • Demonstrates how visual analytics research can be applied to SNA tools for the mass market
  • Includes updated case studies from researchers who use NodeXL on popular networks like email, Facebook, Twitter, and Instagram
  • Includes downloadable companion materials and online resources at https://www.smrfoundation.org/nodexl/teaching-with-nodexl/teaching-resources/
About the Authors xi
Contributors xiii
Preface xv
Acknowledgments xvii
I GETTING STARTED WITH ANALYZING SOCIAL MEDIA NETWORKS
1 Introduction to Social Media and Social Networks
1.1 Introduction
3(1)
1.2 A Historical Perspective
4(1)
1.3 The Rise of Enterprise Social Media Applications
5(1)
1.4 Individual Contributions Generate Public Wealth and Risks
5(1)
1.5 Who Should Read This Book
6(1)
1.6 Applying Social Media to National Priorities
7(1)
1.7 Worldwide Efforts
8(1)
1.8 Practitioner's Summary
9(1)
1.9 Researcher's Agenda
9(2)
References
9(1)
Additional Resources
10(1)
2 Social Media: New Technologies of Collaboration
2.1 Introduction
11(1)
2.2 Social Media Defined
12(1)
2.3 Social Media Design Framework
12(6)
2.4 Social Media Examples
18(9)
2.5 Practitioner's Summary
27(1)
2.6 Researcher's Agenda
28(3)
References
28(1)
Additional Resources
29(2)
3 Social Network Analysis: Measuring, Mapping, and Modeling Collections of Connections
3.1 Introduction
31(1)
3.2 The Network Perspective
32(4)
3.3 Types of Networks
36(1)
3.4 The Network Analysis Research and Practitioner Landscape
37(2)
3.5 Network Analysis Metrics
39(5)
3.6 Social Networks in the Era of Abundant Computation
44(3)
3.7 The Era of Abundant Social Networks: From the Desktop to Your Hand
47(1)
3.8 Tools for Network Analysis
47(1)
3.9 Node-Link Diagrams: Visually Mapping Social Networks
48(1)
3.10 Common Network Analysis Questions Applied to Social Media
48(1)
3.11 Practitioner's Summary
49(1)
3.12 Researcher's Agenda
50(5)
References
50(1)
Additional Resources
51(4)
II NODEXL TUTORIAL: LEARNING BY DOING
4 Installation, Orientation, and Layout
4.1 Introduction
55(1)
4.2 Downloading and Installing NodeXL
56(1)
4.3 Getting Started with NodeXL
56(3)
4.4 Layout: Arranging Vertices in the Graph Pane
59(3)
4.5 Undirected and Directed Graph Type
62(1)
4.6 Working with NodeXL Files
63(1)
4.7 Practitioner's Summary
64(1)
4.8 Researcher's Agenda
65(2)
References
65(1)
NodeXL Papers
66(1)
5 Labeling and Visual Attributes
5.1 Introduction
67(1)
5.2 Labeling
67(4)
5.3 Visual Properties
71(6)
5.4 Practitioner's Summary
77(1)
5.5 Researcher's Agenda
77(2)
References
78(1)
6 Calculating and Visualizing Network Metrics
6.1 Introduction
79(1)
6.2 ABCD Network Example
79(1)
6.3 Computing Graph Metrics
80(4)
6.4 Marvel Cinematic Universe Network Example
84(4)
6.5 CSCW 2018 Conference Twitter Network Example
88(5)
6.6 Practitioner's Summary
93(1)
6.7 Researcher's Agenda
93(2)
References
93(2)
7 Grouping and Filtering
7.1 Introduction
95(1)
7.2 U.S. Senate Voting Analysis
96(5)
7.3 CSCW 2018 Twitter Network Analysis
101(8)
7.4 Federal Communications Commission (FCC) Lobbying Coalition Network
109(3)
7.5 Practitioner's Summary
112(1)
7.6 Researcher's Agenda
112(3)
References
112(1)
Additional Resources
113(2)
8 Semantic Networks
8.1 Introduction
115(1)
8.2 Creating the Twitter Gardasil HPV Word Pair Network
115(4)
8.3 Analyzing Word Networks
119(2)
8.4 Visualizing Work Networks
121(2)
8.5 Visualizing Computing Dissertation and Thesis Connections
123(1)
8.6 Practitioner's Summary
123(1)
8.7 Researcher's Agenda
123(6)
References
124(1)
Suggested Reading
125(4)
III SOCIAL MEDIA NETWORK ANALYSIS CASE STUDIES
9 Email: The Lifeblood of Modern Communication
9.1 Introduction
129(1)
9.2 History and Definition of Email
130(1)
9.3 Email Networks
131(1)
9.4 What Questions Can Be Answered by Analyzing Email Networks?
132(1)
9.5 Working with Email Data
133(3)
9.6 Cleaning Email Data in NodeXL
136(2)
9.7 Analyzing Personal Email Networks
138(4)
9.8 Creating a Living Org-Chart with an Organizational Email Network
142(4)
9.9 Historical and Legal Analysis of Enron Email
146(1)
9.10 Practitioner's Summary
147(1)
9.11 Researcher's Agenda
148(1)
References
148(1)
10 Thread Networks: Mapping Message Boards and Email Lists
10.1 Introduction
149(1)
10.2 Definition and History of Threaded Conversation
149(2)
10.3 What Questions Can Be Asked
151(1)
10.4 Threaded Conversation Networks
152(2)
10.5 Identifying Important People and Social Roles in the CSS-D Q&A Reply Network
154(4)
10.6 Understanding Groups At Ravelry
158(1)
10.7 Practitioner's Summary
159(1)
10.8 Researcher's Agenda
159(2)
References
160(1)
Further Reading
160(1)
11 Twitter: Information Flows, Influencers, and Organic Communities
11.1 Introduction
161(1)
11.2 Defining Your Topic-Networks: Formulating a Social Media Monitoring Query
161(1)
11.3 Twitter Data Collection
162(1)
11.4 The Raw Data Layout
163(3)
11.5 Network Analysis
166(6)
11.6 Visualization
172(3)
11.7 Analysis of Content
175(2)
11.8 Share Your Work on the NodeXL Graph Gallery
177(1)
11.9 Practitioner's Summary
177(1)
11.10 Researcher's Agenda
177(2)
References
178(1)
Suggested Reading
178(1)
12 Facebook: Public Pages and Inter-Organizational Networks
12.1 Introduction to Facebook: The Social Graph of 2 Billion People
179(1)
12.2 Facebook Networks
180(1)
12.3 Organizational Networks: Fan Pages
180(5)
12.4 Practitioner's Summary
185(1)
12.5 Researcher's Agenda
185(2)
References
186(1)
Suggested Reading
186(1)
13 YouTube: Exploring Video Networks
Itai Himelboim
Jen Golbeck
Bryan M. Trude
13.1 Introduction
187(1)
13.2 What is YouTube?
188(1)
13.3 YouTube's Structure
189(1)
13.4 Networks in YouTube
189(1)
13.5 Hubs, Groups, and Layers: What Questions Can Social Network Analysis of YouTube Answer?
190(1)
13.6 Importing YouTube Data into NodeXL
191(2)
13.7 Preparing YouTube Network Data
193(1)
13.8 Analyzing YouTube Networks
194(8)
13.9 Practitioner's Summary
202(1)
13.10 Researcher's Agenda
203(2)
References
203(1)
Suggested Reading
203(2)
14 Wiki Networks: Connections of Culture and Collaboration
Howard T. Welser
Nina Cesare
Derek Hansen
Md. Mahbub Or Rahman Bhuyan
14.1 Introduction
205(2)
14.2 Key Features of Wiki Systems
207(2)
14.3 Wiki Networks from Edit Activity
209(2)
14.4 Using the NodeXL Media Wiki Page Network Importer to Access Wikipedia Networks
211(1)
14.5 Understanding Topics Through Page-to-Page Connections
212(5)
14.6 Analyzing the Structure of Discussion Page Interaction
217(5)
14.7 Choosing the Right Sample Frame for Your Wiki Research
222(1)
14.8 Practitioner's Summary
222(1)
14.9 Researcher's Agenda
223(2)
References
223(2)
Index 225
Derek L. Hansen is an associate professor in the Information Technology program at Brigham Young University. Prior to that he was at the University of Marylands iSchool where he directed the Center for the Advanced Study of Communities and Information and was a member of the Human Computer Interaction Lab. Dr. Hansen completed his PhD from the University of Michigans School of Information where he was an NSF-funded interdisciplinary STIET Fellow focused on understanding and designing effective online socio-technical systems. Dr. Hansens research and teaching focuses on understanding and designing social technologies, tools, and games for the public good. He has received over $2 million in grants (as a PI or co-PI) to help develop and test novel technical interventions with interdisciplinary collaborators including educational Alternate Reality Games (AGOG, DUST, The Tessera), Playable Case Studies (Microcore), Citizen Science games (Floracaching, Odd Leaf Out), and exercise games (Fitplay Games, various pervasive play games). He has also worked with the Social Media Research Foundation and Human Computer Interaction Lab (HCIL) to develop and evaluate NodeXL, a free network analysis and visualization tool that runs in Microsoft Excel and is designed to help community analysts make sense of the mass of data available via social media tools such as Twitter, Facebook, and email. Ben Shneiderman is a professor in the Department of Computer Science and founding director of the Human-Computer Interaction Laboratory at the University of Maryland. He was elected as a Fellow of the Association for Computing (ACM) in 1997, a Fellow of the American Association for the Advancement of Science (AAAS) in 2001, and a Fellow of the National Academy of Inventors (NAI) in 2015. He is a past recipient of the ACM SIGCHI Lifetime Achievement Award. Dr. Shneiderman is the author and coauthor of many books, technical papers, and textbooks. Marc Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. He founded and managed the Community Technologies Group at Microsoft Research in Redmond, Washington and led the development of social media reporting and analysis tools for Telligent Systems. Smith leads the Connected Action consulting group and lives and works in Silicon Valley, California. He is a co-founder of the Social Media Research Foundation which is dedicated to Open Tools, Open Data, and Open Scholarship related to social media.

Smiths research focuses on computer-mediated collective action: the ways group dynamics change when they take place in and through social cyberspaces. Smiths goal is to visualize these social cyberspaces, mapping and measuring their structure, dynamics and life cycles. At Microsoft, he developed the Netscan” web application and data mining engine that allows researchers studying Usenet newsgroups and related repositories of threaded conversations to get reports on the rates of posting, posters, crossposting, thread length and frequency distributions of activity. Smith applied this work to the development of a generalized community analysis platform for Telligent, providing a web based system for groups of all sizes to discuss and publish their material to the web and analyze the emergent trends that result. Dr. Smith is an adjunct faculty at the College of Information Studies at the University of Maryland and a Distinguished Visiting Scholar at the Media-X Program at Stanford University. Dr. Itai Himelboim is director of the SEE Suite, Social media Engagement & Evaluation and Associate Professor, Advertising, at the University of Georgia, He studies the role social media plays in news, politics and international communication. Through applying network analysis, he examines political talk and information flow. His research involves computer-mediated social networks and their implications for political communication, international communication and the news.