IEEE International Conference on Computing, Analytics and Security Trends (CAST-2016). College of Engineering, Pune.

1. Credibility, Identity Resolution, and
Privacy on Online Social Media
IEEE International Conference on Computing, Analytics
and Security Trends (CAST-2016)
COEP
Dec 20, 2016
Ponnurangam Kumaraguru (“PK”)
Associate Professor
ACM Distinguished Speaker
fb/ponnurangam.kumaraguru, @ponguru

2. Who am I?
– Associate Professor, IIIT-Delhi
– Ph.D. from School of Computer Science,
Carnegie Mellon University (CMU)
– Research interests
-Social Computing, Computational Social Science,
Complex Networks pertaining to Human Behavior,
specifically in the context of Security & Privacy
– Co-ordinate and manage Precog,
precog.iiitd.edu.in
– ACM Distinguished Speaker
2

3. https://www.youtube.com/channel/UCHWDvG
Dh4QjWbV79bM2neSg
3

4. 4
What we dabble with!

5. 5
https://arxiv.org/pdf/1611.01911v2

6. 6

7. 7

8. 8
http://labs.precog.iiitd.edu.in/killfie/

9. 9
http://precog.iiitd.edu.in/blog/2016/11/killfie-journey/

10. 10
http://precog.iiitd.edu.in/Publications_files/aa-spyingextensions.pdf

11. 11

12. 12

13. 13

14. Non-trustworthy Content
FAKE
14
$
RUMORS

15. Methodology
15

16. Training Data
– 500 Tweets per event
– Used CrowdFlower
16
Event Tweets Users
Boston Marathon Blasts (2013) 7,888,374 3,677,531
Typhoon Haiyan / Yolanda (2013) 671,918 368,269
Cyclone Phailin (2013) 76,136 34,776
Washington Navy yard shootings (2013) 484,609 257,682
Polar vortex cold wave (2014) 143,959 116,141
Oklahoma Tornadoes (2013) 809,154 542,049
Total 10,074,150 4,996,448

17. Credibility Modeling
17
Feature set Features (45)
Tweet meta-data
Number of seconds since the tweet; Source of tweet (mobile / web/
etc); Tweet contains geo-coordinates
Tweet content (simple)
Number of characters; Number of words; Number of URLs; Number of
hashtags; Number of unique characters; Presence of stock symbol;
Presence of happy smiley; Presence of sad smiley; Tweet contains
`via'; Presence of colon symbol
Tweet content (linguistic)
Presence of swear words; Presence of negative emotion words;
Presence of positive emotion words; Presence of pronouns; Mention
of self words in tweet (I; my; mine)
Tweet author Number of followers; friends; time since the user if on Twitter; etc.
Tweet network
Number of retweets; Number of mentions; Tweet is a reply; Tweet is a
retweet
Tweet links WOT score for the URL; Ratio of likes / dislikes for a YouTube video

18. Implementation

19. Feedback by Users
19

20. v

21. Harvard (1839) – Harvard – Harvard – Harvard – MIT –
Northwestern – UIUC – WUSL – CMU (2009) – IIITD
(2015)
21

22. http://twitdigest.iiitd.edu.in/TweetCred/
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23. De-duplicating audience
Social audience = 437,632 + 153,000 + 805,097 or less??
23

24. Challenges
24
ProfessionalOpinion
Dating
Heterogeneous OSNs
Personal
Degree of Details
Quality and descriptive personal
And professional information
Little personal information
Descriptive opinions
Attribute Evolution
Time
Information evolved on one but
not on other
{jainpari, Bangalore}
Registration with same
information on both OSNs
{paridhij, New Delhi}

25. Generic Identity Resolution
25
Extract
available &
discriminative
features
Candidate
Identities
IDENTITY SEARCH IDENTITY LINKING
Pairwise
Comparisons

26. Heuristic Identity Search
26
cerc.iiitd.ac.in
Profile
Content
Self-mention
Network
Syntactic
and Image
Search Linking
If self-identified /
returned by
more than one
search method
No
Yes
Candidate
Identities
name,
location,
username
mobile no,
post,
friends,
followers
Paridhi Jain, Ponnurangam Kumaraguru, and Anupam Joshi. 2013. @I seek ‘fb.me’: Identifying Users across Multiple Online Social
Networks. In Proceedings of the 22nd International Conference on World Wide Web, WWW ’13 Companion. ACM, New York, NY, USA,
1259- 1268. DOI=http://dx.doi.org/10.1145/2487788.2488160 [Honorable Mention Award}

27. Harvard (1839) – Harvard – Harvard – Harvard – MIT –
Northwestern – UIUC – WUSL – CMU (2009) – IIITD
(2016)
27

28. 28

29. 29
How many of you have posted
mobile numbers on Online Social
Networks?
How many of you have seen
mobile numbers being posted on
Online Social Networks?

30. Sample posts
30

31. Sample posts
31

32. Sample posts
32

33. Sample posts
33

34. Data statistics
– Twitter: 12th October 2012 – 20th October 2013
– Facebook: 16th November 2012 – 20th April 2013
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Numbers Category +91 Category 0 Category void Total
Twitter Facebook Twitter Facebook Twitter Facebook Twitter Facebook
Mobile
Numbers
885 2,191 14,909 8,873 25,566 25,294 41,360 36,358
User
profiles
1,074 2,663 17,913 9,028 31,149 25,406 49,817 36,588

35. 35

36. SocialCaller App
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https://play.google.com/store/apps/details?id=com.ayush.socialcaller&hl=en

37. Takeaways
– Online Social Media is a different beast in
terms of privacy, identity, and credibility
-Research / technologies should be developed
– Multiple interesting research, engineering,
and innovation waiting to be done
– Interested in hosting students – B.Tech.,
M.Tech., Ph.D.
37

38. 38
https://www.facebook.com/PreCog.IIITD/