Resources and annexes to the paper **"[Towards Visual Explorations of Forums' Collective Dynamics in Learning Management Systems](tex_draft.pdf)"**
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
## Images
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@@ -74,34 +74,34 @@ The images in the paper are sometime small. We offer high enough resolution ima
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.
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
## 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.
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 (<spanclass="timestamp-wrapper"><spanclass="timestamp"><2019-05-22 mer.></span></span>):
The exemples of visualisations are accessible online at the following adresses (<spanclass="timestamp-wrapper"><spanclass="timestamp"><2019-05-22 mer.></span></span>):
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### Hangout chats:
### Hangout chats:
Visualizations on <https://observablehq.com/@maliky/conversation-visualization-v2>
Visualizations on <https://observablehq.com/@maliky/conversation-visualization-v2>
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### Moodle visualization:
### Moodle visualization:
Visualizations on <https://observablehq.com/@maliky/playing-with-moodle-data>
Visualizations on <https://observablehq.com/@maliky/playing-with-moodle-data>
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### 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.
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>
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@@ -44,9 +44,9 @@ There is also [[https://idev.kone.ci/visu/uvci/conv7][this link]] to the onlined
[[file:images/evolution.png]]
[[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.
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
** 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.
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:
*** Hangout chats:
Visualizations on https://observablehq.com/@maliky/conversation-visualization-v2
Visualizations on https://observablehq.com/@maliky/conversation-visualization-v2
