https://github.com/rpytel1/mathoverflow-network-analysis

Analysis of the mathoverflow user interaction data using networks
https://github.com/rpytel1/mathoverflow-network-analysis

mathoverflow network-analysis networkx stackoverflow

Last synced: 24 days ago
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Analysis of the mathoverflow user interaction data using networks

• Host: GitHub
• URL: https://github.com/rpytel1/mathoverflow-network-analysis
• Owner: rpytel1
• Created: 2019-04-13T12:17:20.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2019-04-23T11:13:39.000Z (almost 6 years ago)
• Last Synced: 2024-11-17T11:56:02.191Z (3 months ago)
• Topics: mathoverflow, network-analysis, networkx, stackoverflow
• Language: Jupyter Notebook
• Homepage:
• Size: 38.1 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# tudelft-complex-networks #

Complex networks project (2019).

### New ideas? ###

- [ ] think about multilayer network? 

- [ ] for certain time window we can define questions

- [ ] roboustness attack: investigate how removal of few most popular answering users would collapse the network

and num of questions would be unanswered

- [ ] activity driven network 

## Final ideas ##

1. Basic analysis of undirected network (metrics, if scale-free network etc)(Almost done)(RSK)

2. Define user types and try to find patterns which define user type by comparing directed and undirected graph (RSK)

3. Thread detection(NCH)

4. Motifs analysis (implementation + look for patterns between layers and networks)(RPY)

5. Popularity prediction (VSK)

Notes: 

- check for each node in undirected graph as interaction(compare directed and undirected)

- analyze motifs (algorithms from paper) and perform similar analysis as they did

- GROUND TRUTH: no of posts per year(fitting distribution to the interactions we can calculate)

- Finally analyze patterns on MathExchange and then later check if it generalize to others (super-user and ask-ubuntu)