- Overview:
- In this project, 8 Million Github user's activity data was collected, filtered, and analyzed. The user profiles are modelled, and the typical user behavior patterns are identified by applying unsupervised clustering on the follow network.
- Part 1:
- 8 Million Github user's activity data was extracted from historical user activity database on Google BigQuery platform
- Follow network are built using user's activity data
- Various topological features and aggregated behavior features were calculated using social network analysis techniques, and the user profolios were generated
- Part 2:
- User profolio data was carefully explored and cleaned.
- Un-supervised culstering was executed to identify typical user behavior patterns of Github users.
-
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Data analytics project on large scale social-network analysis
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