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Social Network Dynamics Xiang Zuo 1 Jeremy Blackburn 2 Nicolas Kourtellis 3 John Skvoretz 1 and Adriana Iamnitchi 1 ID: 603200 Download Presentation

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ties indirect tie link indirect ties link tie formation paths prediction diffusion information strength social measurements hop datasets networks

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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.

Shom More....
By: celsa-spraggs
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Type: Public

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