Social Network Dynamics Xiang Zuo 1 Jeremy Blackburn 2 Nicolas Kourtellis 3 John Skvoretz 1 and Adriana Iamnitchi 1 ID: 603200
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Slide1
The Influence of Indirect Ties on Social Network Dynamics
Xiang Zuo1, Jeremy Blackburn2, Nicolas Kourtellis3, John Skvoretz1 and Adriana Iamnitchi1
1University of South Florida – Florida, USA 2Telefonica Research – Barcelona, Spain 3Yahoo Labs – Barcelona, Spain
Slide2
Network Dynamics
2
http://not-ionic.tumblr.com/Slide3
What Is a
n Indirect Tie?An indirect tie is defined as a relationship between two individuals who have no direct relation but are connected through other node(s) in the network.3Slide4
Why
Study Indirect Ties?4
Indirect ties are known to be a strong force shaping the network dynamics.We lack quantitative studies of the influence of indirect ties on network dynamics, especially for social distances longer than 2 hops.Slide5
Outline
5
Datasets and indirect tie measurementsIndirect ties and link predictionTiming of link formationIndirect ties and information diffusion pathsSlide6
Datasets
6
NetworksNodesEdgesAPLEdge weightsDOTTF22,4069,7204.2[1-21,767]12300 daysIE4102,765
3.6[1-191]9
90 days
CA-I
348
595
6.1
[1-52]
14
N/A
CA-II
1,127
6,690
3.4
[1-127]
11
N/A
Datasets vary from online gaming networks to face-to-face interaction networks and co-authorship networks Slide7
Indirect Tie Measurements
7
Jaccard Coefficient (J)Adamic-Adar (AA)Social Strength (SS)Slide8
Outline
8
Datasets and indirect tie measurementsIndirect ties and link predictionTiming of link formationIndirect ties and information diffusion pathsSlide9
Using Indirect Ties for Link Prediction
9
Can we use a 2-hop (or 3-hop) indirect tie between nodes that are not directly connected to predict whether a link will form between them?Slide10
Link Prediction Results
10
NetworksnClassifier MetricPrecision Recall F-Measure AUCTF22Decision Tree (J48)SS0.75±0.0120.74±0.0080.74±0.0080.77±0.009
AA
0.71±0.004
0.71±0.004
0.71±0.004
0.71±0.006
J
0.51±0.007
0.51±0.006
0.50±0.008
0.51±0.008
IE
2
SS
0.84±0.013
0.84±0.002
0.84±0.002
0.87±0.001
AA
0.69±0.002
0.69±0.002
0.68±0.003
0.70±0.003
J
0.69±0.007
0.68±0.005
0.68±0.001
0.68±0.004
TF2
3
SS
0.63±0.020
0.63±0.010
0.62±0.010
0.64±0.030
IE
3
SS
0.64±0.010
0.63±0.010
0.63±0.010
0.66±0.010
Indirect ties are able to predict the formation of links even when the social path is longer than 2.Slide11
Outline
11
Datasets and indirect tie measurementsIndirect ties and link predictionTiming of link formationIndirect ties and information diffusion pathsSlide12
Timing of Link Formation
12Link formation delay: the interval between the time when the link formation conditions are met and the time when the link forms.
Is there any connection between the strength of an indirect tie and the delay of link formation?Slide13
Link Formation Delay Definition
13Slide14
Tie Classification
14
Classify indirect ties into strong and weak with three criteria:Slide15
Tie Strength vs. Link Delay
15
33% (strong) vs. 7% (weak)Strong indirect ties form direct links quicker both in 2 and 3 hops.Slide16
Outline
16
Datasets and indirect tie measurementsIndirect ties and link predictionTiming of link formationIndirect ties and information
diffusion pathsSlide17
Can Indirect Ties Predict Diffusion Paths?
17Given that a user received a piece of information at time step t, can we predict which other users will receive this information at time step t+2 or t+3?Slide18
Experimental Setup
18 Ground TruthLinear Threshold (LT) model in LTScale the value of as ω
[1-10] in CA-I ω [1-30] in CA-II ω [1-100] in TF2 Path Prediction Calculate strength of indirect tiesRank a user’s 2(3)-hop neighbors based on the calculated strength values
Define a cut-off threshold to select the user’s topN
indirect neighbors
CompareSlide19
Prediction Evaluation (2-hop paths)
19Slide20
Prediction Evaluation (3-hop paths)
20
Indirect ties can serve as a predictor for information diffusion paths.Slide21
Summary
Indirect ties have the power to predict link formation between people at social distances greater than 2.The strength of an indirect tie positively correlates to the speed at which a direct link forms between the two people.Indirect ties can serve as a predictor for diffusion paths in social networks.21Slide22
22
Thanks!Distributed Systems Grouphttp://www.cse.usf.edu/dsg/Slide23
Social Strength Metrics (Cntd…)
23
32ijk
m
7
3
i
j
k
m
3/(7+3)=0.3
7/(3+7)=0.7
2/(2+3)=0.4
3/(3+7)=0.3
SS
2
(i,m)=0.2775
SS
2
(i,m)=0.2775
3
2
i
j
k
m
7
3
i
j
k
m
0.3
0.3
0.4
SS
2
(m,i)=0.44
Backup Slides
0.7Slide24
Indirect Ties Infer Diffusion Paths
24
Rank indirect relationship according to the score calculated by indirect tie measurements.
w
here q is inverse proportional to
ω
User A’s
2-
hop
contacts’
rank:
Example
e.g., in CA-I.