𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗥𝗲𝘃𝗶𝗲𝘄
Finding groups within a network is hard. Networks contain millions of connections. You need to find patterns to understand them.
Community detection helps you group nodes together. These groups share more connections than the rest of the network. This process works in social media, biology, and fraud detection.
This review covers the main methods used today:
- Modularization methods look for high density within groups.
- Random walk methods follow paths to see where nodes cluster.
- Spectral methods use math to find splits in the data.
- Information theoretic methods measure how much data stays in a group.
The paper provides a visual survey of these techniques. You see how different algorithms behave on real data.
Read the full study to learn more about these structures.
Source: https://dev.to/paperium/network-community-detection-a-review-and-visual-survey-5430
Optional learning community: https://t.me/GyaanSetuAi