@I seek 'fb.me': Identifying Users across Multiple Online Social Networks

@I seek ‘fb.me’: Identifying Users across Multiple

Online Social NetworksWorkshop on Web of Linked En11es (WoLE)

Paridhi Jain¶, Ponnurangam Kumaraguru¶, Anupam Joshi*¶Indraprastha Ins1tute of Informa1on Technology (IIIT-‐Delhi)

*University of Maryland, Bal1more County (UMBC)

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13/05/13 @I seek ‘fb.me’: Identifying Users across Multiple Online Social Networks

Motivation

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Multiple OSNs

Multiple Identities

Difficult to manage? Difficult to find?

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Motivation

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Multiple OSNs

Multiple Identities


Social Aggregation site

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Motivation

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Multiple OSNs

Multiple Identities


Social Aggregation site Friend Finder?Malicious user?Influen1al user?User of interest?

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Motivation

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Multiple OSNs

Multiple Identities

Identity Resolution Problem


Social Aggregation site Friend Finder?Malicious user?Influen1al user?User of interest?

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Identity Resolution

• For a user I, given a user identity IA on a social network A, find user identity IB on social network B.

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Alice ??

{IA} {IB}

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Identity Resolution = Identity Search + Identity Matching

• Identity Search

For a user I, given her identity IA on a social network A, and a search parameter S, find the set of identities IBj on social network B such that S(IA) ⋍ S(IB).

{IA,S} {IB1, ... IBj, ... , IBN} = Q

• Identity Matching

Given a user identity IA on a social network A, a set of candidate identities Q on social network B, and a match function M, locate an identity pair (IA, IBj) such that M(IA, IBj) = max{M(IA, IB1), M(IA, IBN)}

{IA, Q, M} {IA, IBj} {IB}

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Research Gaps?� Till now, focus on bePer iden1ty matching algorithms

� Only profile aPributes (private and public) for Iden1ty Search

� Limita1ons of Profile Search -‐� Restric1ve search, owing to non-‐availability of common aPributes across networks. [Gender on Facebook, but not on TwiPer]

� Search with Limited aPributes → Large candidate set size → Intensive Iden1ty Matching computa1on

� Users may choose different profile aPributes → Miss out correct iden1ty in the candidate set

� LiPle research on using content and network aPributes to search for candidate iden11es

� Extensive use of both private and public aPributes. Need user authoriza1on for iden1ty search

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Proposal� Include content and network aPributes as search parameters

� Access only publicly accessible aPributes

� Focus on two popular social networks -‐ TwiPer and Facebook

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Contribution� Proposed novel iden1ty search methods on social networks

� Our iden1ty resolu1on methods return correct Facebook iden1ty for 39% TwiPer users within top-‐2 ranks

� We observe an increase in accuracy of iden1ty resolu1on by 11.6% owing to inclusion of content and network iden1ty search, along with improvised profile search

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Methodology

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?

?

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? Syntactic and Image

Search Match

If self-identified / returned by

more than one search method

No

Yes

Candidate Identities

Manual Verification

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Identity Matching

� Syntac1c Matching� Jaro Distance comparison between username and name� Example: {alice123, jane_alice}, {Alice Naura, Alice N. Janice}

� Image Matching

where hIA and hIBj are the RGB histograms of the profile image and Ns represent histogram size of IA

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Profile Search

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Self -‐ Iden1fica1on

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Content Search

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Self-mention Search

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Network Search

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Instance,

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Instance,

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Public Friend List of a user extracted from public feeds

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Integrated System -

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Evaluation

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Method (543 users) # of users % Accurate

Profile (P) 205 37.7

Content (C + SM) 34 6.3

Network (N) 1 0.2

Finding Nemo 212 39

Dataset # of usersSocial Graph API 543

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Evaluation

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Method (543 users) # of users % Accurate

Profile (P) 205 37.7

Content (C + SM) 34 6.3

Network (N) 1 0.2

Finding Nemo 212 39

Search Algorithm # of users identified Accuracy

P (without URL) 149 27.4%

P (with URL) + C + N + SM

149+56+6+1 = 149+71

27.4% +11.6%

Dataset # of usersSocial Graph API 543

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Mean Average Precision

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↓

Matching algorithm MAP Score

Image (profile image) 0.83

Syntactic (username) 0.76

Syntactic (name) 0.80

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Demo

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hPp://www.youtube.com/watch?v=-‐AFsCtKwO0c

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http://www.youtube.com/watch?v=-AFsCtKwO0c

http://www.youtube.com/watch?v=-AFsCtKwO0c


Take away

Inclusion of content and network a9ributes for iden1ty search not only improves iden1ty resolu1on accuracy but returns

correct Facebook iden1ty within top-‐2 ranks for majority of the TwiPer users.

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Current and Future Work

� Extend the social networks to search for a given iden1ty. Example, Google+, Foursquare, etc.

� Extend the search methods to include social-‐network specific features

� Find mul1ple (fake) iden11es of users within social networks

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Questions?

[email protected], [email protected], [email protected]

Paper: hPp://precog.iiitd.edu.in/publica1ons.html

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mailto:[email protected]




http://precog.iiitd.edu.in/publications.html

http://precog.iiitd.edu.in/publications.html

For any further informa1on, please write to [email protected]

precog.iiitd.edu.in

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http://precog.iiitd.edu.in/

http://precog.iiitd.edu.in/

@I seek 'fb.me': Identifying Users across Multiple Online Social Networks

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