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Do we compute the graph in backend (once every x time) or dynamically in frontend ? Maybe half on the back (preprocessing data) and half on the front (for display) ?
What does the dataset looks like (in backend if computation in backend; in frontend if compute in frontend) ?
What the graph should look like ? Should it be static (like a picture) or dynamic (like a video or an interactive object) ?
Current idea:
Display videos as nodes (maybe squared that become video icons when zooming)
The more users have seen (compared at least once) a video, the bigger the node
Under 3 users having seen the video => display as a dot (no video icon)
Maybe some shadow or border of color according to global tournesol score (black -> red -> yellow -> green)
Edges (links between nodes) if comparisons between two videos
More comparisons between two videos => Larger the edge
Try to make all egdes length the same with graph layout algorithm
That will obviously not be possible (graph isn't planar)
Comparisons made per multiple persons to have the priority to be of the fixed length (weight force between videos by comparisons count) => for large comparisons not to be stretched too far away
Color comparisons with red to green color gradient (green on the + side, red on the - side)
Color intensity depends on average comparison value between videos (0=gray, 1=grayish color, ... 10=bright color)
I imagine with this display to see groups where videos have been compared a lot to eachother (so maybe groups by video airing date or theme), and globaly red and green zones indicating where good and bad video are. I expect some moon like dots all around (all the less compared videos), displaying all the diversity available on Tournesol
Demo picture incoming, feel free to give others visualization styles idea or to suggest improvements to this idea above
This is an idea suggesting during a recent retrospective session.
TODO:
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