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Big Data, Network Analysis Big Data, Network Analysis

Big Data, Network Analysis - PowerPoint Presentation

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Big Data, Network Analysis - PPT Presentation

Week 13 How is date being used Predict Presidential Election Nate Silver httpadagecomarticlecampaigntrailnatesilverselectionpredictionsawinbigdatayorktimes238182 Predict Pregnancy Target ID: 565685

network networks data social networks network social data analysis http ties systems actors density information www patterns amp science individual web directed

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Slide1

Big Data, Network Analysis

Week 13Slide2

How is date being used

Predict Presidential Election - Nate Silver

http://adage.com/article/campaign-trail/nate-silver-s-election-predictions-a-win-big-data-york-times/238182

/

Predict Pregnancy - Target

http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did

/Slide3

Why Networks?

Why is the role of networks in CS, Info Science, Social Science, Physics, Economics, and Biology expanding?

More Data

Rise of the Web and Social Media

Shared vocabulary between (very different fields)Slide4

Reasoning about Networks

How do we reason about networks?

Empirical

: Look at large networks and see what we find

Mathematical Models

: probabilistic, graph theory

Algorithms

for

analyzing graphs

What do we hope to achieve from the networks?

Patterns and statistical properties of network data

Design principles and models

Understand why networks are organized the way they are (predict behaviors or networked systems)Slide5

Why networks?

Network data is increasingly available:

Large on-line computing applications where data can naturally be represented as a network

Online communities:

Facebook

Communications:

Instant Messenger

News and Social Media:

Blogging

Also in systems biology, health, medicine, …Slide6

Networks: Rich Data

a – Internet

b

– Citation network

c

– World Wide Web

d – sexual network

e – dating networkSlide7

Networks

Information networks:

World Wide Web: hyperlinks

Citation

Blog

Social networks:

Organizational

Communication

Collaboration

Sexual

Collaboration

Technological networks:

Power grid

Airline, road, river

Telephone

InternetAutonomous systemsSlide8

What is Social Network Analysis?

Network analysis is the study of social relations among a set of actors. It is a

field of study, not just a method.

Social network analysis involves theorizing, model building and empirical research focused on uncovering the patterning of links among actors. It is concerned also with uncovering the antecedents and consequences of recurrent patterns.

(Linton Freeman

)Slide9

The Network Perspective

People

(nodes)

Ties

(edges)Slide10

Ties in a social network

Directed or undirected

Simplex or multiplex

Valued or unvalued

7Slide11

What is a Social Network?

A set of dyadic ties, all of the same type, among a set of actors

Actors can be persons, organizations, groups

A tie is an instance of a

specific

social relationship

11Slide12

Network Relations

Among

Individuals

Kinship

Role-based (friend of)

Cognitive/Perceptual (knows, aware of)

Affiliations

Affective (likes, trusts)

Communication

Among Organizations

Buy from / Sell to

Owns shares of

Joint ventures

12Slide13

Key Perspectives in Social Network Analysis

Focus on

relationships

between actors rather than just the attributes of actors.

Interdependent view

rather than atomistic (individualist) view of social processes and effects.

Social structure

affects substantive outcomes (which is a philosophical departure from other traditions)

13Slide14

Interdisciplinary Field of Study

Computer Science

Designing and understanding complex network structures

Mathematics, Physics

Methods, complex systems analysis

Social Science (Sociology, Social Psychology, Economics)

Theories and measurement of social networks, using networks to understand human behavior

14Slide15

Multiple Levels of Analysis

Individual Level

How does individual position in a network affect various outcomes for the individual?

Systems Level

How does the network structure as a whole affect outcomes for various tasks?

15Slide16

Network Data Collection

Common Types:

Survey

Interviews

Affiliation/membership records

Behavioral (e.g., observation of communication patterns)

Experiments

16

Data obtained through manyeyes and graphed: http://www.esv.org/blog/2007/01/mapping.nt.social.networksSlide17

Types of Network Data

One mode Two mode

Whole network Egocentric

17

A

B

C

A

B

School ASlide18

Non-directed versus Directed Graphs

18

A

B

C

A

B

CSlide19

Analyzing Social Networks

A

B

C

D

A

-

1

1

1

B

1

-

1

0

C

1

1

-

1

D

1

0

1

-

19

A

D

B

C

Simple Adjacency MatrixSlide20

Some Key Principles in Social Networks

Degree

The degree to which actors are connected directly to each other by

cohesive bonds

Density

The

proportion of direct ties in a network relative to the total number

possible

Centrality

a group of metrics that aim to quantify the "importance" or "influence" (in a variety of senses) of a particular node (or group) within a

network

20Slide21

Degree in Social Networks

21Slide22

Density in Social Networks

22

Low Density

High Density / Integrated

Radial

(Valente)Slide23

Centrality in Social Networks

Degree Centrality

Closeness Centrality

Betweeness Centrality

23Slide24

Why all of this sudden interest?

The strength of the

Strength of Weak Ties

argument.

Granovetter (1973)

Argues that

weaker

peripheral ties build heterogeneous networks, which in turn provide access to new and useful information.

Heterogeneity through weak-ties widely accepted as a

good thing

for communication

Access to jobs

Access to other opportunities

Helps distribute ideas, innovations

24Slide25

Ted Talk

The

hidden

influence

of social

networks

http

://youtu.be/2U-tOghblfESlide26

Social Networks

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

5etSid8G6EU

http://www.youtube.com/watch?v=PThAriHjk10&playnext=1&list=PL05CC28C66163B00D&feature=

results_mainSlide27

Slides adapted from:

Jure

Leskovec

, Stanford CS224W: Social and Information Network Analysis

ure

Leskovec

, Stanford CS224W: Social and Information Network Analysis

http

://bit.ly/

Y7fALp