Social network analysis and growth recommendations for DataScience SG community
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This document discusses different social networks and connections between users on a platform. It describes user friendship networks colored based on inactivity levels. It also describes user like networks, with edges representing likes between friends and non-friends. Finally, it discusses user comment networks derived from the like network connections.
Social network analysis and growth recommendations for DataScience SG community
- 6. Smaller nodes represent long inactive periods Colored from blue (inactive for more than 3 months) to red (active in last one month)
- 9. with locked positions from friendship network Yellow edges- liking posts from non-friends Red edges - liking posts from friends
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- 11. User-User like network Colored via Markov Clustering Nodes sized by number of likes given
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- 13. User-user like network Examples of one-off likes who did not like any other posts.
- 17. User-user comment connection, using frozen positions from like network previously. Colored by Markov Clustering from the like network
- 18. User-user comment network. Colored by Markov Clustering from the like network
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- 24. ■ Use substrings to extract full web links ■ Use Python scripts to “unmask” the redirect link
- 25. ■ Copy the code above to macro ■ The new function called “Title” will be generated ■ Drag down as usual
- 27. ■ Remove punctuation ■ Remove Numbers ■ Remove stopwords such as “analyst,data,singapore” and the website name such as ”straits time” ■ Perform LDA get top 4 topics and top 7 most frequency words in the topic
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