PT|EN
Formal Analysis of Social Networks
Courses Master in Information and Enterprise Systems
Cod: 22147
Department: DCET
ECTS: 7
Scientific area: Computer Engineering
Total working hours: 210
Total contact time: 40

The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on an unprecedented scale, and the development of new tools has allowed us to extract knowledge from networks of many different kinds.

To exemplify the concepts the Microsoft's NodeXL free, open-source plug-in for use with Excel provides users to instant graphical representations of the relationships that exist between complex networked data.

measuring social networks
social networks clustering
social networks process and visualization

At end of this course each student shall be able to:
• Recognize the role and importance of social networks in the context of Web computing environments;
• Identify the key techniques and tools to extract knowledge of social networks;
• Apply these techniques in multidisciplinary experimental cases.

1 - Analyzing Social Media Networks
• Measuring and Mapping
• Network Modeling
• Networks Processes
2 – R and NodeXL Tutorial
• Calculating and Visualizing Network Metrics
• Preparing Data and Filtering
• Clustering and Grouping
• Social Media Network Analysis Case Studies: Email, Twitter, WWW, YouTube, Wiki Networks

- Networks: An Introduction by Mark Newman, Oxford University, 2010 ISBN-10: 0199206651.

- Networks, Crowds, and Markets: Reasoning About a Highly Connected World by David Easley, Jon Kleinberg, Cambridge University Press (2010), ISBN-10: 0521195330

-Social Network Analysis, by John P Scott, Publisher: Sage Publications Ltd; 2nd edition (2000), ISBN-10: 0761963383.

- Analyzing Social Media Networks with NodeXL: Insights from a Connected World by  Derek Hansen, Ben Shneiderman, Marc A. Smith, Editora: Morgan Kaufmann (2010), ISBN-10: 0123822297.

E-learning

Evaluation is made on individual basis and it involves the coexistence of two modes: continuous assessment (60%) and final evaluation (40%). Further information is detailed in the Learning Agreement of the course unit.