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Commits (2)
# Table of Contents
1. [CSEDU-2019](#org11e87c6)
1. [Images](#org7aaa272)
2. [Code](#orge31e9d0)
1. [Hangout chats:](#org123942e)
1. [CSEDU-2019](#org3888225)
1. [Images](#orgd8d275a)
2. [Code](#org6ac6b51)
1. [Hangout chats:](#org4de6f5a)
2. [Moodle visualization:](#org8bd4c7e)
3. [Coursera](#org26e6959)
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# CSEDU-2019
Resources and annexes to the paper **"[Towards Visual Explorations of Forums' Collective Dynamics in Learning Management Systems](tex_draft.pdf)"**
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## Images
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At the top (a) is half of compound yearly actor-actor network. The three bottom images (b), (c) and (d) are closeup around actor 642 during the quarters of the year.
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## Code
The images above have been generated using code that ressembles closely the one below.
The images above have been generated using code from the Code folder <Code/>
It is mainly code to preprocess the data files that will then be processed in d3.js.
The exemples of visualisations are accessible online at this adresses (<span class="timestamp-wrapper"><span class="timestamp">&lt;2019-05-22 mer.&gt;</span></span>):
The exemples of visualisations are accessible online at the following adresses (<span class="timestamp-wrapper"><span class="timestamp">&lt;2019-05-22 mer.&gt;</span></span>):
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### Hangout chats:
Visualizations on <https://observablehq.com/@maliky/conversation-visualization-v2>
1. Moodle visualization:
Visualizations on <https://observablehq.com/@maliky/playing-with-moodle-data>
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### Moodle visualization:
Visualizations on <https://observablehq.com/@maliky/playing-with-moodle-data>
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2. Coursera
### Coursera
Use the file <Code/SNA-Coursera17/> folder to scrape the data from a Coursera course and then wrangle the data to make the visualisation.
The visualisation requires graph<sub>tool.py</sub>
Check the <Code/SNA-Coursera17/README.md>
Use the file <Code/SNA-Coursera17/> folder to scrape the data from a Coursera course and then wrangle the data to make the visualisation.
The visualisation requires graph_tool.py
Check the <Code/SNA-Coursera17/README.md>
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[[file:images/evolution.png]]
At the top (a) is half of compound yearly actor-actor network. The three bottom images (b), (c) and (d) are closeup around actor 642 during the quarters of the year.
** Code
The images above have been generated using code that ressembles closely the one below.
The images above have been generated using code from the Code folder [[file:Code/]]
It is mainly code to preprocess the data files that will then be processed in d3.js.
The exemples of visualisations are accessible online at this adresses (<2019-05-22 mer.>):
The exemples of visualisations are accessible online at the following adresses (<2019-05-22 mer.>):
*** Hangout chats:
Visualizations on https://observablehq.com/@maliky/conversation-visualization-v2
**** Moodle visualization:
*** Moodle visualization:
Visualizations on https://observablehq.com/@maliky/playing-with-moodle-data
**** Coursera
*** Coursera
Use the file [[file:Code/SNA-Coursera17/]] folder to scrape the data from a Coursera course and then wrangle the data to make the visualisation.
The visualisation requires graph_tool.py
Check the [[file:Code/SNA-Coursera17/README.org]]
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