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Introduction to Social Network Analysis

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This workshop will introduce some of the main principles and techniques of Social Network Analysis (SNA). We will use examples from organizational and social media-based networks to understand concepts such as network density, diameter, centrality measures, community detection algorithms, etc. The session will also introduce Gephi, a popular program for SNA. Gephi is a free and open-source tool that is available for both Mac and PC computers.

By the end of the session, you will develop a general understanding of what SNA is, what research questions it can help you answer, and how it can be applied to your own research. You will also learn how to use Gephi to visualize and examine networks using various layout and community detection algorithms.

Instructor’s Bio: Dr. Anatoliy Gruzd is a Canada Research Chair in Social Media Data Stewardship, Associate Professor at the Ted Rogers School of Management at Ryerson University, and Director of Research at the Social Media Lab. Anatoliy is also a Member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists; a co-editor of a multidisciplinary journal on Big Data and Society; and a founding co-chair of the International Conference on Social Media and Society. His research initiatives explore how social media platforms are changing the ways in which people and organizations communicate, collaborate and disseminate information and how these changes impact the norms and structures of modern society.

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Introduction to Social Network Analysis

  1. 1. Introduction to Social Network Analysis (SNA) ANATOLIY GRUZD GRUZD@RYERSON.CA @GRUZD C A N A D A R E S E A R C H C H A I R A S S O C I AT E P R O F E S S O R , T E D R O G E R S S C H O O L O F M A N A G E M E N T D I R E C TO R O F R E S E A R C H , S O C I A L M E D I A L A B R Y E R S O N U N I V E R S I T Y with Gephi
  2. 2. Dr. Anatoliy Gruzd Canada Research Chair & Director of Research OurTeam Philip Mai, JD Director of Business & Communications 6-10 Undergraduate, Master /MBA & PhD students (Business, CS, Sociology, Information & Psychology) Drs. Jenna Jacobson & Priya Kumar Post Doctoral Fellows Collaborators from across Canada, the US, UK, Netherlands, HK, Korea, and Brazil. 2 About the Social Media Lab SocialMediaLab.ca @SMLabTO
  3. 3. Conference & Workshops 400+ Authors * 250+ Attendees * 28 Countries Annual International Conference on Social Media & Society #SMSociety SocialMediaAndSociety.org
  4. 4. Download Slides and Practice Dataset http://bit.ly/asac18 Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 4
  5. 5. Outline ◦ Brief Introduction to SNA ◦ Case Study: Organizational Networks Hands-on part with Gephi: ◦ Sample Dataset: Massively Open Online Course for Educators (MOOC-Eds) ◦ Exploratory Analysis using Network Visualization Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 5
  6. 6. Gephi Network visualization, data preparation, exploration Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 6 Download from https://gephi.org/users/download/ Requires Java JDK http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html
  7. 7. SNA Text http://faculty.ucr.edu/~hanneman/nettext/ 7
  8. 8. 8 Social Network Analysis (SNA) Nick Rick Dick • Nodes = People • Ties = Edges = Relations Anatoliy Gruzd (@gruzd) Social Network Analysis
  9. 9. 9 With networks we can answer questions such as … • What group/individuals stand out? • Are there important connections? • What is the “health” of the organization? • How different are two groups/individuals or the same group at two different times? Anatoliy Gruzd (@gruzd) Social Network Analysis
  10. 10. 10 Using SNA in the learning context • Identify students who might need extra attention/help from the instructor • Find active group members who often take a leadership role in a group • Identify peer-help Student Instructor Student Group LeaderStudent Student
  11. 11. 11 SNA Terminology
  12. 12. 12 Directed vs Undirected Networks Example: Communication Network (directed) Nick Rick Dick • Nodes = People • Ties = “Who talks to whom” • Tie strength (weight)= The number of messages exchanged between individuals mutual/ reciprocal Anatoliy Gruzd (@gruzd) Social Network Analysis
  13. 13. Case Study Organizational Networks
  14. 14. N is for Network: Mapping Organizational Changes Nancy Steffen-Fluhr, Regina Collins, Babajide Osatuyi, Anatoliy Gruzd NJIT-led and NSF-funded project (2009-2013) Advancing Women at NJIT through Collaborative Research Networks 14
  15. 15. “Universities and corporations are not merely buildings and balance sheets…. They are relational entities--webs of interaction and perception whose complex structure is largely invisible to the people embedded in them.” (O'Reilly, 1991) Anatoliy Gruzd (@gruzd) Social Network Analysis 15
  16. 16. Network structure drives institutional change… facilitating (or retarding) innovation—maintaining (or altering) norms, including norms of gender and race. 2000 2005 2008 Anatoliy Gruzd (@gruzd) Social Network Analysis 16
  17. 17. “Network inequality creates and reinforces inequality of opportunity” (Christakis & Fowler, 2009) Understanding network dynamics is especially important for underrepresented minorities and women who can easily spend their entire careers on the periphery, far away from the flow of information at the core. 17
  18. 18. Being IN the Loop means: • access to unpublished research • invitations to join grant initiatives • the opportunity to vet one’s work • support for intellectual risk-taking Being OUT of the loop makes it harder to accumulate social capital which, in turn, has a negative effect on retention and advancement. 18
  19. 19. NETWORK CENTRALITY “The more paths that connect you to other people in your network, the more susceptible you are to what flows within it.” (Christakis & Fowler, 2009) Hypothesis: If women faculty members are less centrally located than male faculty, they will incur greater information- foraging costs and have fewer opportunities to signal their value as organizational players, a difference that may constitute a structural constraint for advancement. Anatoliy Gruzd (@gruzd) Social Network Analysis 19
  20. 20. NJIT ADVANCE is using SOCIAL NETWORK ANALYSIS (SNA) to create new mapping tools that will give junior faculty & their mentors an aerial view of the organizational landscape …a “GPS System for Career Management.” “Can’t see the forest for the trees.” SNA Mapping Anatoliy Gruzd (@gruzd) Social Network Analysis 20
  21. 21. Phase One: Building a Faculty Publications Database (DB) 2208 author names 7225 publications Primary data acquisition method: data-mining of Scopus DB Interface Modules: Author/Publications Co-Authors Statistics Anatoliy Gruzd (@gruzd) Social Network Analysis 21
  22. 22. Phase Two: Preparing to Map Changing Network Connections Among NJIT Co-Co-authors 2000-2008 463 tenured/tenured-track STEM faculty Mapping Tools: NJIT DB UCINET ORA • UCINET https://sites.google.com/site/ucinetsoftware/downloads • ORA (Organizational Risk Analyzer) from CMU http://www.casos.cs.cmu.edu/projects/ora/
  23. 23. Phase Three: Using UCINET to test hypotheses about network structure, collaboration, and career advancement. Defining SNA Terms: DEGREE CENTRALITY indicates well-connected people who can directly reach many people in the network. BETWEENNESS CENTRALITY reflects the extent to which an individual has the ability to control the flow of information in the network. EIGENVECTOR CENTRALITY reflects the extent to which an individual is connected to well-connected people in the network. Anatoliy Gruzd (@gruzd) Social Network Analysis 23
  24. 24. Homophily Male faculty are much more likely to co-author with other male faculty than with women faculty Anatoliy Gruzd (@gruzd) Social Network Analysis 24
  25. 25. Network Centrality and Retention For women faculty, Eigenvector centrality was a much stronger predictor of retention than number of publications Female Eigenvector Centrality = Retention Anatoliy Gruzd (@gruzd) Social Network Analysis 25
  26. 26. Network Centrality and Retention For women faculty, Eigenvector centrality was a much stronger predictor of retention than number of publications Female Eigenvector Centrality = Retention Collaboration and Advancement in Rank Assistant and associate professors who co-authored more with other NJIT faculty members exhibited greater upward movement in rank than those who co-authored less. More collaboration = Rise in academic rank (promotion) Anatoliy Gruzd (@gruzd) Social Network Analysis 26
  27. 27. Phase Four: Data Visualization Using ORA to Create and Analyze Network Maps Defining Terms: Ego Network: a focal node and the nodes to whom it is directly connected (alters) plus the ties among the alters. Anatoliy Gruzd (@gruzd) Social Network Analysis 27
  28. 28. Phase Four: Data Visualization Using ORA to Create and Analyze Network Maps Defining Terms: Ego Network: a focal node and the nodes to whom it is directly connected (alters) plus the ties among the alters. Whole-Network Analysis maps “the occurrence and non-occurrence of relations among all members of a population” (Garton,1997) Anatoliy Gruzd (@gruzd) Social Network Analysis 28
  29. 29. SNA Can Support Institutional Transformation Bibliometric data —more and more easily accessible on a national/global scale—is a valid proxy for real-world faculty networks. Drawing on such data, university policy makers can use new SNA tools to… ▪ track changes in organizational health, ▪ identify emerging leaders or isolated backwaters ▪ compare the relative advancement of selected groups/individuals. Anatoliy Gruzd (@gruzd) Social Network Analysis 29
  30. 30. Hands-On Part: Gephi Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 30
  31. 31. Massive Open Online Courses (MOOCs) ▪ A large scale reimagining of traditional online courses ▪ A typical MOOC consists of 1,000+ students ▪ Since “The Year of the MOOC” (NY Times, 2012), interest has been steadily rising Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 31
  32. 32. SNA may help to … Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 32
  33. 33. Practice Dataset: MOOC-Eds ‘MOOC-Eds are designed specifically for professional educators and follow the guidelines for effective professional learning and a special set of design principles: multiple voices, self-directed learning, peer-supported learning and job-connected learning.’ Anatoliy Gruzd (@gruzd) Kellogg, S., & Edelmann, A. (2015). Massively Open Online Course for Educators (MOOC-Ed) network dataset. British Journal of Educational Technology. http://doi.org/10.1111/bjet.12312 SOCIAL NETWORK ANALYSIS 33
  34. 34. Practice Dataset: MOOC-Eds Downloadable from Harvard Dataverse Anatoliy Gruzd (@gruzd) https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZZH3UB SOCIAL NETWORK ANALYSIS 34
  35. 35. Communication Networks Online interactions are represented as a graph where nodes = online participants, and edges (ties) = communication patterns or other relation types among participants. Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 35
  36. 36. Practice Dataset: MOOC-Eds 2 Network Files + 2 Node Attribute Files Anatoliy Gruzd (@gruzd) https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZZH3UB Today’s focus SOCIAL NETWORK ANALYSIS 36
  37. 37. Practice Dataset: MOOC-Eds Communication Network as a Matrix Anatoliy Gruzd (@gruzd) USER N19 replied to USER N219 SOCIAL NETWORK ANALYSIS 37
  38. 38. Practice Dataset: MOOC-Eds List of Class Participants and Their Attributes Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 38
  39. 39. Gephi Network visualization, data preparation, exploration Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 39 Download from https://gephi.org/users/download/ Requires Java JDK http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html
  40. 40. 1. Open File File > Open Anatoliy Gruzd (@gruzd)40
  41. 41. 2. Run a layout algorithm Try “Fruchterman Reingold” Followed by “Expansion” Anatoliy Gruzd (@gruzd)41
  42. 42. 2. Run a layout algorithm Try “Fruchterman Reingold” Followed by “Expansion” 445 nodes, 1978 edges Anatoliy Gruzd (@gruzd)42
  43. 43. 3. Identify Instructors’ network position Under “Nodes”, select the “Partition” tab and then “facilitator” from the drop down menu, and click “Apply” Anatoliy Gruzd (@gruzd)43
  44. 44. 3. Identify Instructors’ network position Under “Nodes”, select the “Partition” tab and then “facilitator” from the drop down menu, and click “Apply” Anatoliy Gruzd (@gruzd)44
  45. 45. 4. Hide Instructor nodes Under “Filters”, double click “Attributes” -> “Equal”; Drag & drop “facilitator” to the Queries section below and click “Select” Anatoliy Gruzd (@gruzd)45
  46. 46. 5. Rerun “Fruchterman Reingold” layout Anatoliy Gruzd (@gruzd)46
  47. 47. 5. Rerun “Fruchterman Reingold” layout Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS47 443 nodes, 1450 edges
  48. 48. Explore Research Questions through Visualizations What factors influence the formation of communication ties in this network? Let’s explore the tendency of some nodes to cluster (homophily) and their network positions (centrality) based on the following attributes: Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 48 Connect Whether participants listed networking/collaboration with others as one of their course goals on the registration form Experience2 Number of years teaching Role Professional role (e.g., teacher, librarian, administrator) Grades Works with elementary, middle, and/or high school students
  49. 49. “Connect” Anatoliy Gruzd (@gruzd)49
  50. 50. “Experience” Anatoliy Gruzd (@gruzd)50
  51. 51. Gephi Tutorials https://gephi.org/users/ Anatoliy Gruzd (@gruzd) SOCIAL NETWORK ANALYSIS 51
  52. 52. References • Steffen-Fluhr, N., Collins, R., Passerini, K., Wu, B., Gruzd, A., Zhu, M., Hiltz, R. (2012). Leveraging Social Network Data to Support Faculty Mentoring: Best Practices. Women in Engineering Program Advocates Network (WEPAN) National Conference, June 25-27, 2012, Columbus, OH., USA. • Osatuyi, B., Steffen-Fluhr, N., Gruzd, A., and Collins, R. (2010). An Empirical Investigation of Gender Dynamics and Organizational Change. The International Journal of Knowledge, Culture and Change Management 10(3): 23-36. Available at http://ijm.cgpublisher.com/product/pub.28/prod.1216 • Steffen-Fluhr, N., Gruzd, A., Collins, R. and Osatuyi,B. (2010). N is for Network: New Tools for Mapping Organizational Change. National Association of Multicultural Engineering Program Advocates (NAMEPA)/ Women in Engineering Program Advocates Network (WEPAN) 4th Joint Conference, April 12-14, 2010, Baltimore, Maryland, USA. Anatoliy Gruzd (@gruzd) Social Network Analysis 52
  53. 53. Introduction to Social Network Analysis (SNA) ANATOLIY GRUZD GRUZD@RYERSON.CA @GRUZD C A N A D A R E S E A R C H C H A I R A S S O C I AT E P R O F E S S O R , T E D R O G E R S S C H O O L O F M A N A G E M E N T D I R E C TO R O F R E S E A R C H , S O C I A L M E D I A L A B R Y E R S O N U N I V E R S I T Y with Gephi

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