Tongji Data Structure Project - Social Network Links Prediction
- Name generator: Name generator
- organizations (schools)
javascript
,python
(+jupyter notebook
)echarts
,bootstrap
,ajax
,networkx
Django
create virtual environment in conda
(env name: social_network)
cd network_demo
conda env create -f environment.yaml
conda activate social_network
enter the folder with manage.py
then start service
cd network_demo
python manage.py runserver
scale background graph by scrolling click on categories at the top of the page
features implemented in echarts
click on cards in the left sidebar, profile displayed on the right sidebar
select Algorithms (default to Intersection
) and Mode (default to All Users
) at the bottom of Detailed infomation
manage your page with control island (UDCP Buttons)
upload your JSON
file at Custom
return to Defalut graph at Default
data generator in folder data\eupho_dataset\dataset_generator.ipynb
As for the name
eupho
, I initially wanted to build up a network with the purpose of displaying sophisticated interpersonal relationships in Animation SeriesSound! Euphonium
. And that's exactly the reason why I tested Japanese names in my demo dataset. The organizations in this network could be schools, clubs, companies or even social groups and person nodes are individuals (characters in the anime :) )
Documenting the profiles of characters in
Sound! Euphonium
is really time-consuming which is not feasible, and actually unnecessary, for a 2-week project. Therefore, I got some random names from name generators on Google. (But I got names ofKituji High School Concert Band
which are listed in the filedata\eupho_dataset\dataset_generator.ipynb
from Season 1 to Season 2.5)
where
Bonus: individual social habits considered. A wide range of friends means less strengthed friendship while deeper friendship expected for individuals who have fewer connections with others. The node would earn higher score if it had a few connections but still shared many nodes with the target.
Official Networkx Implementation
where
Official Networkx Implementation
where 0.8
,