How can I get started with SocialNetworkAnalysis in a short time?

Which teaching materials can be recommended? What kind of analysis software should we start? Which teaching materials can be recommended? What kind of analysis software should we start? Reply: first, there are two ways to analyze the social network: one is liberal arts and the other is sociology. This is to analyze the qualitative analysis and explain some social phenomena on a quantitative basis, the other is partial to science, which usually requires a large amount of data points, and then Performs quantitative analysis and judgment on the topological structure in mathematics, or it will use the Online Social network (Online Social Networks) on the network for large-scale computing. If it is a software party, it is generally the first type. It throws the network into the software to calculate indicators or something. Gephi is recommended for the software. This visualization is very convenient and the effect is very beautiful. It is the same as that of Facebook's data science team. If you want to process large-scale computing, you can use Python's iGraph. It is also an artifact, but it is not as intuitive as Gephi. You need to take a look at the tutorial to learn the syntax.

For the introductory course, there is an eight-week introductory course from the University of Michigan's female teacher on Coursera. There are also many examples of interaction, which are very good, the professor is also a well-known person in the social network analytics field. If you have good English skills, you can read Social Network Analysis (Douban) This book is also popular abroad. If the English is not good, I don't know any teaching materials in China ~

In short, the social network analysis is a big artifact in the research method, because the network structure is everywhere, learning it has a lot of benefits. I am specialized in management, so I recommend social science and academics.

Course A: the difficulty becomes more and more difficult in order. Click the link on the course page and some courses will start again.
1 Network life: Coursera.org It is very basic and easy to understand.
2 Networks, Crowds, and Markets INFO2040x Course Info It is also very simple and involves a wide range of areas, mostly in the computer and economics fields.
3 demographic and network Coursera.org The Chinese version of the second course is a little more difficult and more advanced.
4 Social Network Analysis Coursera.org Some talk about netlogo software, a simulation software, you can skip this part.
5 Social and economical Networks: Models and Analysis Coursera.org Biased economics, multi-derivation, difficult.

Software B: The order is arranged according to the difficulty of getting started. Please download your own google. The manual official website generally has
1. Gephi is free of charge. The pictures are brilliant. The official website provides online Chinese tutorials.
2 NodeX Excel-based plug-ins for ease of use
3 UCINET payment, multi-purpose social science, and powerful statistical functions
4 pajek free, fast processing of large-scale data
5. statnet R packages are difficult to use, but they handle random graph models and dynamic data. There are many extension packages.

C books: sort by difficulty. You can read more references of these books by yourself.
1. Scott, Shen chonglin, and LIU Jun in the social network analysis method (hichina method)
Entry book, not about software
2 Overall Network Analysis handout LIU Jun
The usage and recommendation of UCINET are completely introduced. It is used in combination with software 3.
3. interdisciplinary masterpiece series • Spider: Social Network Analysis Technology (version 2nd) Wouter De Nooy, Andrej Mrvar ), vladimir Batagelj, Li Yijia, and Lin Feng (Summary: Book Review trial] books
I fully introduced the usage of pajek, but the software version is a little old, it is 2.05, and the software has been updated 3
4. Social Network Analysis: Methods and Applications; Stanley Wasserman and Catherine Faust; works together, Chen Yu and Sun rainbow; summary: Book Review test] books
Basic book. I suggest you start with it. It's very detailed, not software.
5 networks, groups, and markets: Revealing the principles and mechanisms of action in a highly interconnected world David Esley, Jon kleberger, and Li Xiaoming, wang Weihong and Yang Wenli [Abstract: Book Review trial] books
The author is the speaker of course 2, and the translator is the speaker of course 3. It is very interesting and not about software.
6. Social and economic networks Matthew O. Jackson (Matthew O. Jackson) and Liu maosen [Abstract: Book Review trial] books
The author is the speaker of course 5, which is economical and difficult

I am not very familiar with PS complex networks. I recommend two books from Barabasi and the work of Watts. What is famous in China is Mr. Wang Xiaofan.

My avatar is also painted by Gephi. Update:

If you are interested, you can use the following data for free: Stanford Large Network Dataset Collection.

Data with P2P, wikipedia, amazon IMDB, and other relational networks.

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Python has a package called networkx, which is especially convenient for running network data.

The easiest way to get started is to read wikipidea and find out the various Centrality To understand the PageRank algorithm.

Stanford has a network science database with Facebook, twitter, and other data. If you are familiar with it, you can also run it.

The gephi mentioned above is indeed very convenient, that is, I ran it out with gephi.