Online courses & toolbox



I have uploaded a series of presentations here to introduce the tools of “computational social science”. The content of these presentations are listed as follows:



1. Data collection and analysis using Python

1.1 Scraping and analyzing webpages: collecting website statistics from Google and Alexa

1.2 Connecting APIs: Google API, YouTube Data API, Twitter API, and Alchemy API

1.3 Browser automation: collecting the historical viewing records of YouTube videos

1.4 Bayesian model in natural language processing



2. Data analysis and visualization using R

2.1 Classical methods: ANOVA, correlation, regression, clustering, time series, multilevel analysis

2.2 Network statistics: degree, closeness, betweenness, and Page Rank of  nodes

2.3 Network statistics: average length of path, clustering coefficient, density, and components of  networks

2.4 Network community detection algorithms: leading eigenvector, walk-trap, edge-betweenness, spin-glass, label propagation

2.5 Network visualization: igrah layout functions, multilevel force-based algorithm, phylogenetic tree



3. Data analysis and simulation using Mathmatica

3.1 Data fitting and numerical simulation of various distributions: Gaussian, Exponential, Poisson, Gamma, Log-normal

3.2 Fit long-tail data with maximum likelihood estimation and measuring the fractal dimension of real-world objects

3.3 Markov-based analysis of network data: transitivity, Page Rank, tropical levels, hierarchy index

3.4 Retrieve human behavioral data from online images: statistical figures and satellite maps

3.5 Introduction to Turing machine, cellular automata and the concept of universal computation



4. Constructing agent-base models using Netlogo

4.1  Exploring the competition between Web 1.0 and Web 2.0 sites

4.2 Exploring the origins of alturism

4.3 The dynamic growth model of networks: Small-world model, BA model, and stochastic geometric graph model



5. Data visualization using Processing

5.1 Hierarchical edge bundling of networks

5.2 Animation and swarm intelligence

5.3 L-tree and other fractals



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