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Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Discovering Leaders from Community Actions
Presenter : Wu, Jia-Hao
Authors : Amit Goyal , Francesco Bonchi ,
Laks V. S. Lakshmanan
CIKM (2009)
國立雲林科技大學National Yunlin University of Science and Technology
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
2
Outline
Motivation
Objective
Methodology
Experiments
Conclusion
Personal Comments
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Motivation
We have some interactions with you and me in the internet actives that can be a social networks. like rating songs as in Yahoo! Music or Yahoo! Movies or users
burying gadgets such as cameras , handhelds…
Buy Write
I want to buy.
I want to buy.
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Objective
The authors want to find the leaders and tribe leaders from the social networks and action log.
Buy Write
Leader
Actions log
Tribe Leader
Buy Actions log
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Objective (Cont.)
The authors want to find the leaders and tribe leaders from the social networks and action log.
Social networks
Action log
Propagation of action a
Propagation of action b
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Objective (Cont.)
If we know that there are a small number of leaders who set the trend for various actions. Targeting them for adoption of new products could be profitable to the
companies (Targeted advertising).
Write
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Methodology
Parameters : maximum propagation time threshold
: number of the node in action α
: a number of actions by the user u
Leader
Tribe Leader
Propagation of action a
Propagation of action b
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Methodology (Cont.)
Leadership confidence
Genuineness score of v
Constraint 1.
Constraint 2.
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Methodology (Cont.) – Computing Influence Matrix
Lock Bit Vector
S T V W R
7 6 5 4 3 2 1 0
0 1 0 1 0 1 1 1
Node
InfVec
S T V W R
R 0 1 0 1 0 1 1 1
S 0 1 0 0 0 1 1 0
T 0 0 0 1 0 1 1 0
W 0 0 0 0 0 1 1 0
V 0 0 0 0 0 1 0 0
R
S T
W
V
R W V T S
R 1 1 1 1 1
W 0 1 1 0 0
V 0 0 1 0 0
T 0 1 1 1 0
S 0 1 1 0 1
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Methodology (Cont.) – Propagate
Lock Bit Vector
S T V W R
7 6 5 4 3 2 1 0
0 1 0 1 0 1 1 1
R
S T
W
V
PLock Bit Vector
S TP V W R
7 6 5 4 3 2 1 0
0 1 0 1 1 1 1 1
P
0 0 0 0 1 0 0 0
R
0 1 0 1 0 1 1 1
OR
R
0 1 0 1 1 1 1 1
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Methodology (Cont.) – Update
R
S T
W
V
P Q
Node InfVec
S T V W R
R 0 1 0 1 0 0 1 1
S 0 1 0 0 0 0 1 0
T 0 0 0 1 0 0 1 0
W 0 0 0 0 0 0 1 0
V 0 0 0 0 0 1 0 0
Lock Bit Vector
S T V W R
7 6 5 4 3 2 1 0
0 1 0 1 0 1 1 1
Lock Bit Vector
S Q TP V W R
7 6 5 4 3 2 1 0
0 1 1 1 1 1 1 1
P
0 0 0 0 1 0 0 0
Node InfVec
S T P V W R
R 0 1 0 1 1 0 1 1
S 0 1 0 0 1 0 1 0
W 0 0 0 0 1 0 1 0
OR
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Methodology (Cont.) - Computing
Leaders
Genuineness Leaders
Tribe Leader
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Experiments (Cont.)
75293206280 198671
68241
130514
170467
22380130514
20045
Intelligent Database Systems Lab
N.Y.U.S.T.I. M.
Conclusion
The authors purpose notions of leaders and tribe leaders together with possible additional properties such as confidence and genuineness.
Use the two key operations – update and propagate to search the changes of social network graph.
The result is the first proposal of a framework based on frequent pattern mining for discovering leaders in social networks.