Network Visualization and Analysis

What is Social Network Analysis?

• The study of social relationships among individuals, organizations, or groups
• Examines patterns of connections between social entities and characteristics of the entities themselves

Key Concepts in Social Network Analysis:

• Nodes: entities in a social network (individuals, organizations, or groups)
• Edges: connections between nodes (friendships, collaborations, communication channels)
• Networks: overall structures that emerge from connections between nodes and edges
• Centrality: measures the importance of nodes within a social network (high centrality nodes are important hubs or connectors)
  • Closeness centrality: measures how close a node is to all other nodes
  • Betweenness centrality: measures how often a node lies on the shortest path between other pairs of nodes
• Clustering: measures the degree to which nodes in a network form tightly interconnected groups or clusters

Graphic illustration of the network descriptors degree, triangle, clustering coefficient, closeness centrality and betweenness centrality in a hypothetic network. (Zhang et al., 2016)

Applications of Social Network Analysis:

• Used in humanities, sociology, psychology, business, and computer science
• Analyzes social media networks, organizational structures, spread of disease/information, social influence/persuasion, and identifies key players in a social network

Reference:

Zhang, P., Tao, L., Zeng, X., Qin, C., Chen, S., Zhu, F., Li, Z., Jiang, Y., Chen, W., & Chen, Y. Z. (2017). A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks. Briefings in Bioinformatics, 18(6), 1057-1070.

1. Introduction to Social Network Methods: A comprehensive online textbook that introduces the basics of social network analysis. 
2. UCINET: Software for social network analysis that includes a variety of tools and algorithms for analyzing social networks. 
3. Network analysis with R and igraph: NetSci X Tutorial: This tutorial provides an introduction to social network analysis using igraph package in R (Ognyanova, 2016)
4. Network Analysis and Visualization with R: This online book covers network analysis and visualization techniques using R. It includes examples using various R packages such as igraph, statnet, and visNetwork (Ognyanova, 2021). 
5. Coursera:
   • Social Network Analysis (SNA) by the University of California, Davis: A course on social network analysis that covers topics such as network structure, centrality, and community detection. 
   • Applied Social Network Analysis in Python by the University of Michigan: A course that teaches the basics of social network analysis using Python. 
6. Stanford Network Analysis Project: This website provides a variety of resources on social network analysis, including tutorials, courses, and software tools. The website also hosts the Stanford Network Analysis Platform (SNAP), a general-purpose network analysis and graph mining library in Python. 
7. NodeXL: NodeXL is a free and open-source network analysis and visualization software for Microsoft Excel. The software includes a variety of tools for network analysis, including network metrics, visualization, and automation. 
8. Pajek: Pajek is a software package for analysis and visualization of large networks. The software includes a variety of tools for network analysis, including clustering, blockmodeling, and visualization. 

Reference:

Ognyanova, K. (2016) Network analysis with R and igraph: NetSci X Tutorial. Retrieved from www.kateto.net/networks-r-igraph.

Ognyanova, K. (2021) Network visualization with R. Retrieved from www.kateto.net/network-visualization.

• Networks and the Spread of Ideas in the Past: Strong Ties, Innovation and Knowledge Exchange

• A Research Agenda for Social Networks and Social Resilience

• Socio-economic Relations in Ptolemaic Pathyris: A Network Analytical Approach to a Bilingual Community

• Using Social Media to Extract Information about Chemical Weapons Incidents: A Methodology and Demonstration of Concept from the Civil War in Syria

• Análisis de Redes Sociales : Conceptos y Técnicas para la Investigación Social

• Analyzing Global Social Media Consumption

• Exploring Malicious Hacker Communities: Toward Proactive Cyber Defence

• Interrogating Networks: Investigating Networks of Knowledge in Antiquity

• Netzwerke-Performanz-Kultur: Transdisziplinäre Perspektiven und Wechselseitige Bezüge

• Subjective Well-being and Social Media

  • UCI KDD Archive

• Repository of machine learning datasets for various domains, including classification, regression, and clustering.

  • International Networks Archive

• Current and historical network data sets on communication, trade, tourism, policy issues, migration, and other topics.

  • Stanford Large Network Dataset Collection

• Collection of network datasets for research on social, information, and biological networks.

  • UCINET Datasets

• Datasets for social network analysis, including network measures, demographic variables, and behavioral data.

• Enron Emails
• Reality Mining
• Supreme Court Citation Network Data

• Text Analysis 
• Omeka
• Mapping & GIS

This guide was created by Rachel Liu, she is a Research Data and Digital Scholarship Text and Data Mining Assistant at Van Pelt Library. Rachel is a graduate student in Learning Sciences & Technologies concentrating on Education Data Mining.