This course is designed to quite literally ‘make a science’ out of something at the heart of society: social networks. Humans are natural network scientists, as we compute new network configurations all the time, almost unaware, when thinking about friends and family (which are particular forms of social networks), about colleagues and organizational relations (other, overlapping network structures), and about how to navigate delicate or opportunistic network configurations to save guard or advance in our social standing (with society being one big social network itself). While such network structures always existed, computational social science has helped to reveal and to study them more systematically. In the first part of the course we focus on network structure. This looks as static snapshots of networks, which can be intricate and reveal important aspects of social systems. In our hands-on lab, you will also visualize and analyze a network with a software yourself, which will help to appreciate the complexity social networks can take on. During the second part of the course, we will look at how networks evolve in time. We ask how we can predict what kind of network will form and if and how we could influence network dynamics.
提供：
計算社会科学専門講座カリフォルニア大学デービス校（University of California, Davis）このコースについて
学習内容
Define networks and discover the languages networks use.
Analyze a social network through data wrangling and visualizing a network.
Discuss what mechanisms generate networks.
Examine social networks analysis using case studies.
提供：
カリフォルニア大学デービス校（University of California, Davis）
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
シラバス - 本コースの学習内容
Getting Started and Formalizing Networks
In this module, you will be introduced to the concept of networks. You will be able to define networks and identify how data is transformed and analyzed in a network. You will able be able to discuss how to formalize networks.
Social Network Analysis
In this module, you will be able to discuss the structure of networks and be able to explain how a person can be the center of one. You will be able to discover the different types of language that networks use and be able to identify the three types of network measurements.
Analyzing a Network with Software
In this module, you will begin with a social network analysis lab activity. You will be able to do data wrangling of databases and visualize a network. You will be able to analyze a social network and also be able to examine other social network analysis through case studies.
Network Evolution
In this module, you will be able to identify the different types of social networks. You will be able to discuss what mechanisms generates these different types of networks and you will be able to explain how networks move from being static to dynamic.
レビュー
- 5 stars79.89%
- 4 stars13.75%
- 3 stars2.64%
- 2 stars1.58%
- 1 star2.11%
ソーシャルネットワーク分析 からの人気レビュー
Learned a lot more than expected and Hilbert is a great professor
I enjoyed this course. I began this courses wanting to gain a better understanding of social networks. I leave the course with a better understanding of effective decision making. Thank you.
Excellent course packed with any yet essential concepts for social network analysis.
This course bringg us with many patience many perspectives and concepts in order to understan social networks. I think it was incredible for my own self-learning, and for my future researches.
計算社会科学専門講座について
For more information please view the Computational Social Science Trailer
よくある質問
いつ講座や課題にアクセスできるようになりますか？
この専門講座をサブスクライブすると何を行うことができるようになりますか？
学資援助はありますか？
What do students say after completion?
Since this Specialization is a collective effort from all UC campuses, who teaches it?
さらに質問がある場合は、受講者ヘルプセンターにアクセスしてください。
