├── assets
└── images
│ ├── jupyter-server.png
│ └── UKDS_Logos_Col_Grey_300dpi.png
├── LICENSE
├── installation.md
└── README.md
/assets/images/jupyter-server.png:
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/assets/images/UKDS_Logos_Col_Grey_300dpi.png:
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/LICENSE:
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1 | MIT License
2 |
3 | Copyright (c) 2020 UK Data Service Open
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
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/installation.md:
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1 | # Installation
2 |
3 | These instructions guide you through the process of installing Python and other packages (e.g., Jupyter Notebook) on your machine.
4 |
5 | ### Install Python
6 |
7 | The easiest means of installing Python is to download the free Anaconda distribution of the programming language:
8 | * Windows download
9 | * Linux download
10 | * Mac download
11 |
12 | Follow the guidance provided by Anaconda or watch this video guide by King's College London (note: refers to Windows installation).
13 |
14 | ### Running Python
15 |
16 | Anaconda provides various ways of running Python on your machine. We prefer using Jupyter Notebook for writing and documenting our code.
17 | To launch Jupyter notebook, open your Command Line Interface (CLI) and type the following:
18 | ```
19 | jupyter notebook
20 | ```
21 |
22 | For example, to launch Jupyter Notebook on a Windows machine:
23 | 1. In the search bar in the bottom-left corner of your screen, type *cmd* and press `enter`.
24 | 2. With the command prompt open, type *jupyter notebook* and press `enter`.
25 | 3. After a few seconds, you should see the following screen in your web browser:
26 | 
27 |
28 | From this screen you will be able to create new Jupyter notebooks, as well open existing ones.
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/README.md:
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1 | 
2 |
3 | # Computational Social Science
4 |
5 | ### Training Series
6 |
7 | The UK Data Service is pleased to release open learning materials from its training series: *Computational Social Science* (previously known as *New Forms of Data for Social Science Research*). Vast swathes of our social interactions and personal behaviours are conducted online and/or captured digitally. Our use of social media platforms such as Facebook, Twitter and Instagram generates astounding amounts of data, much of which is available from these platforms if you have the right programming skills. Snapshots of our daily lives are routinely captured and aggreagted into large, rich administrative datasets. Websites can be scraped and marshalled into statistically-usable datasets, and documents aggregated into large corpora of text information that can be mined for interesting patterns (e.g., through sentiment analysis). Thus, computational methods for collecting, processing and analysing new forms of data are an increasingly important component of a social scientist’s toolkit.
8 |
9 | ### Materials
10 |
11 | We have provided sample code, webinar recordings and slides, reading lists, FAQs and more for each of the topics covered under the *Computational Social Science* training series:
12 | * **Agent-based Modelling**
13 | * **Web-scraping for Social Science Research**
14 | * **Programming for Social Science Research**
15 | * **Being a Computational Social Scientist**
16 | * **Text Mining**
17 | * **Social media/network Data**
18 |
19 | We have also written guidance for installing Python and other packages on your machine: [Instructions]
20 |
21 | ### Acknowledgements
22 |
23 | We are grateful to UKRI through the Economic and Social Research Council for their generous funding of this training series.
24 |
25 | ### Further Information
26 |
27 | * To keep up to date with upcoming and past training events: [Events]
28 | * To get in contact with feedback, ideas or to seek assistance: [Help]
29 |
30 | Thank you and good luck on your computational social science journey!
31 |
32 | Dr Julia Kasmire
33 | UK Data Service
34 | University of Manchester
35 |
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