New Foundations in Digital Chinese Studies

Digital Tools Preparation for ESSCS


To attend the summer school, you will need to bring your own computer. Some softwares are “trans-OS” (operating system), but some softwares only runs on a specific OS (e.g., Windows). In the form below, we ask you to select the OS on which your computer operates:

Mac – Mac OS – Version:
PC – Windows – Version
PC – Linux – Version


In the course of the summer school, you will be using different standalone or online applications. Yo will find below the list of items to download and install on your computer or of accounts to be opened on online applications.

Paul Vierthaler

As for necessary software, I generally like to teach using the Anaconda distribution of Python  which comes bundled with everything people need to follow along.
If we decide to include topic modelling, then participants would also need to download MALLET and have java installed on their computers.


Geographical Information Systems
Please install QGIS

Liu Jun

The workshop will use the following software and python script and dataset will be shared later.

  1. Anaconda. We will only use Jupyter Notebook in Anaconda.
  2. Gephi : an open-source network analysis and visualization software package

Gephi needs Java to function. If you don’t have it on your computer, Gephi asks you to install it.


Network Analysis
For PC only
Ucinet (free 90-day trial version)
For Mac and PC

Marilyn Levine will rely on Ucinet and Orange, while Cécile Armand and Christian Henriot will rely on Cytoscape. If you are a Mac user, please make sure to install Cytoscape

Donals Sturgeon

The main setup required would be:
1. Create a free account on ctext

2. (Optional) For participants with some basic knowledge of Python, install the ctext API module described here (i.e. run “pip install ctext”)

3. (Optional) Install a font supporting rare Chinese characters in Unicode, as described here

In order to participate fully, a Windows/Mac/Linux device with a mouse is needed, along with either Firefox or Chrome.


Anaconda’s open-source Distribution is the easiest way to perform Python/R data science and machine learning on a single machine. (19 kB)


Machine learning for language toolkit

Chinese Text Project (471 kb)


Chinese Text Project API wrapper (7 kB)