Structual Trend Analysis for Online Social Networks Ceren Budak Divyakant Agrawal Amr El Abbadi...
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Transcript of Structual Trend Analysis for Online Social Networks Ceren Budak Divyakant Agrawal Amr El Abbadi...
Structual Trend Analysis for Online Social Networks
Ceren Budak Divyakant Agrawal Amr El AbbadiScience,UCSB SantaBarbara,USA
Reporter: Qi Liu
What to do?
Trend
traditional
structural
coordinate
uncoordinate
What’s new?
• Structural trend definition• Reducing to local triangles counting• Sampling tech for online detection
From where?
• A temporal view• Using spatial properties• Counting, streaming and semi-streaming
Define it!
• Directed G=(N,E)• ejiϵE => ni is one neighbor of nj
• ni mentions Tx => <ni, Tx>
Traditional:Coordinate: Uncoordinate:
High scores for coordinated trend
• Large number of pairs of connected nodes• Large number of mentions• For a complete graph, favors a uniform
distribution• In a power law graph, biased toward
influential nodes
Example for complete graph
f(Tx) = f(Ty) = 2Ng(Tx) = 3N(N-1) g(Ty) = 4N(N-1)
1
N+1
2
2
2 2
Tx Ty
1
1
Example for power law graph
f(Tx) = f(Ty) = K+N-1g(Tx) = 2K(N-1) g(Ty) = 2K+2N-4
Tx
Ty
K
111
1
11K
Significance Validation
• Model-Based Validation– Independent Trend Formation Model• pi,x: external influence
• qi,j,x: internal influence
– Nearest Neighbor model• u: probability from 2 to 1• k: pairs of connected nodes per step
• Analysis-Based Validation
Coordinated differs from traditional
• Spearman rank correlation coefficient(SRCC)– – [-1, +1]
• Average precision–
• difference
What topics detected?
• Vary p and q• Using different score functions• Results:
App: Sybil Attack Detection
• Ranking of Ty: co>tr>un• Breakpoints may means attack• Small p,q and few Sybil nodes, big effect
Analysis-Based Validation
• Twitter data: 467 million posts, 20 million users, spanning 7 months
• 230m posts, 2.7m users, 2960495 hashtags
Extraction
Tr vs Co vs Un
Something new about twitter data
• Choose 60th to 100th topics• Findings: – coordinated trend: 7694 users, 21.5 edges on
average; – uncoordinated trend: 21114 users, 8.6 edges
Prefuse
Hashtag categories effect
• 7 categories: political, technology, celebrity, games, idioms, movies, music and none
Incremental Counting Algorithm
• For a coming <nl,Tx>
•
Reducing to count local triangles
• A directed multi-graph G’ = (N’,E’)• N’ = T U N, E’ = Et U Ef
Sampling tech
• How to work?• Correctness:–
– Xx = Countx / (ps)^2, : triangles sharing edges
Conclusion
• Two trend definitons• A reduction• Sampling tech
THE ENDTHANKS!