The document discusses a summer school on social network analysis, highlighting its applications in friend recommendations, information flow optimization, and identifying influencers. It also addresses challenges such as data collection, user behavior modeling, and distinguishing between real and fake accounts. The takeaway emphasizes the power of social network analysis for business and government applications, while acknowledging the numerous challenges and opportunities present in the field.

1. Social Network Analysis:
Applications & Challenges
Summer School on Social Computing
June 30, 2018
Ponnurangam Kumaraguru (“PK”)
IIIT {D, H}
TEDx & ACM Distinguished Speaker
Linkedin/in/ponguru/
fb/ponnurangam.kumaraguru
@ponguru

2. 2

3. Manish’s Lecture
– Clustering coefficients
– Power law
– Small world
– Kleinberg’s model
– ….
3

4. 4

5. Growth of Social Media
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6. Top sites Alexa…
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7. 7
2009

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10. 10

11. What is available in social media?
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12. What is available in social media?
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13. Potential applications
– Recommend friends / WTF
– Analyze and improve information /
communication flow
– Identify criminal and terrorist networks
– Identify influencers (Manish will also cover)
– Finding the hidden connections
-Shadow profiles
– Optimize the structure and capacity of
telephone / mobile networks
– …..
13

14. Centrality measures
– Degree
-How many to reach directly?
-E.g. How many have collaborated with Prof.
Pushpak? How many has he collaborated with?
– Betweenness
-Connecting directly 2 different people / networks
-E.g. Arts & CS
– Closeness
-How quickly can this node reach all nodes?
-Information given, to reach among all participants
– Eigenvector
-How well connected to other well connected nodes
-Well cited author who is cited by other well cited
authors
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15. To understand users / customers
– “Show me who your friends are and I’ll tell
you who you are?”
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16. To understand users / customers
– “Show me who your friends are and I’ll tell
you who you are?”
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17. To understand users / customers
– “Show me who your friends are and I’ll tell
you who you are?”
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18. To understand users / customers
– Interest graph
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19. WTF / Recommendations….
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20. 20
Recommendations / Advertising

21. 21
Recommendations / Advertising

22. Recommendations / Advertising
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23. Information flow?
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faculty@lists.iiit.ac.in
faculty@iiitd.ac.in

24. Security applications
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Leader? 2nd in command?

25. Predicting Churning
– What is Churning?
-"Customer churn is nothing but change and turn
in which customer terminates the existing
service and joins service provided by other
service providers. By analyzing the social
networks and activities of customers on social
networks we can predict the churning
customers."
– Examples
-Leaving Airtel and going to Vodafone
-Leaving Netflix and going to Amazon Prime
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26. Wordnet (Dr. Pushpak’s lecture)
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27. Wordnet (Dr. Pushpak’s lecture)
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29. 29

30. Solving Societial problems
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31. Innovation
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32. Productivity
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33. Depression
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34. Answers
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35. Answers
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36. Movies
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40. What is the problem with this?
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41. Challenges
– Very hard to collect, store, and analyze data
-Rate limits
-Large size
-Ego-network
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42. Challenges
– Understanding users / modeling their
interests, behavior
-Manipulated profile information
-Multiple accounts
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43. Challenges
– Understanding the content / meaning
-Sentiment
-Sarcasm
-Emojis
-Code-mixed
-….
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44. Challenges
– Fake / Bot vs Real
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45. Challenges
– Fake / Bot vs Real
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46. Challenges
– Who’s Who / Identity in multiple networks
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https://www.facebook.com/ponnurangam.kumaraguru

48. 48
https://twitter.com/ponguru

49. 49
https://www.linkedin.com/in/ponguru/

50. De-duplicating audience
Social audience = 437,632 + 153,000 + 805,097 or less??
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51. Takeaways
– Social Network Analysis is a power tool
– Business / Government can use the analysis
to their benefits
– You should use it for your benefits J
-You tried doing analysis on your accounts?
– Lots of challenges and opportunities!
– Will be happy to interact more, if needed
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52. 52
pk@iiitd.ac.in
http://precog.iiitd.edu.in/
https://fb.com/ponnurangam.kumaraguru
@ponguru
Linkedin/in/ponguru/