Social Networks AnalysisCourse code: 150611 | 6 ECTS credits
Level of Studies:Undergraduate applied studies
Year of Study:2
Goal:Understanding general concepts and tecnological infrastructure of social networks and social computing; acquiring theoretical and practical knowledge related to the social networking; introduction to the data analysis and information searching in social networks.
Outcome:After successfuly completed course, the student should be able to understands general concepts and tecnological infrastructure of social networks and social computing. Student should be able to search and analyse data in social networks, use and take part in develop of modern tecnologies related to social networks and partitive web.
Contents of the course
Introductory lecture. Basic terms.
Development of WWW. WEB 2.0 and WEB 3.0.
Types and caracteristics of social networks.
Open source initiative. Open data, open content. .
Social network data analysis.
Big data analysis.
Social network analysis (graph theory and social network).
Social processing of information. Information searching and navigation.
Practical instructions in computer laboratories: follow theoretical lessons. Practical work with platforms for creating private social networks. Practical work with social network analysis tools. Course sillabus follows recomendations of IEEE/ACM Computing Curriculum: IT2008 IT body of knowledge: WS. Social software.
Textbooks and References
Tara Calishain, Rael Dornfest, Google trikovi, Kompjuter biblioteka, 2006.
Hiroshi Ishikawa, Social Big Data Mining, CRC Press, 2015.
Matthew A. Russell, Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites, O'Reilly, 2011.
D. Easley and J. Kleinberg, Networks, Crowds, and Markets: Reasoning about a Highly Connected World. Cambridge University Press, New York, NY, USA, 2010.
M. Tsvetovat and A. Kouznetsov, Social Network Analysis for Startups: Finding connections on the social web, O’Reilly Media, 2011.