- From www.coursera.org
Social Network Analysis
- Self-paced
- Free Access
- Бесплатный сертификат
- 9 Sequences
- Introductive Level
Course details
Syllabus
Week 1: What are networks and what use is it to study them?
Concepts: nodes, edges, adjacency matrix, one and two-mode networks, node degree
Activity: Upload a social network (e.g. your Facebook social network into Gephi and visualize it ).
Week 2: Random network models: Erdos-Renyi and Barabasi-Albert
Concepts: connected components, giant component, average shortest path, diameter, breadth-first search, preferential attachment
Activities: Create random networks, calculate component distribution, average shortest path, evaluate impact of structure on ability of information to diffuse
Week 3: Network centrality
Concepts: betweenness, closeness, eigenvector centrality (+ PageRank), network centralization
Activities: calculate and interpret node centrality for real-world networks (your Facebook graph, the Enron corporate email network, Twitter networks, etc.)
Week 4: Community
Concepts: clustering, community structure, modularity, overlapping communities
Activities: detect and interpret disjoint and overlapping communities in a variety of networks (scientific collaborations, political blogs, cooking ingredients, etc.)
Week 5: Small world network models, optimization, strategic network formation and search
Concepts: small worlds, geographic networks, decentralized search
Activity: Evaluate whether several real-world networks exhibit small world properties, simulate decentralized search on different topologies, evaluate effect of small-world topology on information diffusion.
Week 6: Contagion, opinion formation, coordination and cooperation
Concepts: simple contagion, threshold models, opinion formation
Activity: Evaluate via simulation the impact of network structure on the above processes
Week 7: Cool and unusual applications of SNA
Hidalgo et al. : Predicting economic development using product space networks (which countries produce which products)
Ahn et al., and Teng et al.: Learning about cooking from ingredient and flavor networks
Lusseau et al.: Social networks of dolphins
Activity: hands-on exploration of these networks using concepts learned earlier in the course
Week 8: SNA and online social networks
Concepts: how services such as Facebook, LinkedIn, Twitter, CouchSurfing, etc. are using SNA to understand their users and improve their functionality
Activity: read recent research by and based on these services and learn how SNA concepts were applied
Prerequisite
None.
Instructors
- Lada Adamic - School of Information, Center for the Study of Complex Systems
Editor
L'Université du Michigan (UM, UMich ou simplement Michigan) est une université publique de recherche située à Ann Arbor, dans le Michigan, aux États-Unis. Fondée en 1817, l'université est la plus ancienne et la plus grande du Michigan.
La mission de l'université du Michigan est de servir les habitants du Michigan et le monde entier en occupant une place prépondérante dans la création, la communication, la préservation et l'application des connaissances, de l'art et des valeurs académiques, et en formant des dirigeants et des citoyens qui défieront le présent et enrichiront l'avenir.
Platform
Coursera - это цифровая компания, предлагающая массовые открытые онлайн-курсы, основанные учителями компьютеров Эндрю Нгом и Стэнфордским университетом Дафни Коллер, расположенные в Маунтин-Вью, штат Калифорния.
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