Social life networks presentation at fb 110713

and�Middle of the Pyramid�

Ramesh Jain With

Several Collaborators

1.  Networks 2.  Computing Networks 3.  Social Networks 4.  Social Life Networks 5.  Major Challenge: Micro-events to Situations 6.  Our approach 7.  Going Forward

  Different media and information sources   Strongly emerging participatory culture   Collective knowledge and intelligence of

society

  People   Things   Events

  Document created by Humans.   Text, Music, Movies

  Data collected by Humans   Photos, Audio, …

Documents, Data, Events

  Events happen.   Most documents describe events and objects in those.   Most data is collected for events.

  Facebook, Twitter, Google +, …   Sensor networks

  Billions of sensor getting connected

  Ambitious projects   Planetary Skin by Cisco and NASA   Smart Planet by IBM

  Can things in real world be connected to other things?

  Does this even make sense?

  Five Senses connect us to the world.   We use our sensors (vision, audio, …) to

experience the world.   Sensors could be the interface between the

Cyberspace and the Real World.   Sensors are placed for ‘detecting events’.

  How do you decide what sensors to put at any place?

  Would you put a sensor if nothing interesting ever happens at a place?

Causal

Experiential

Structural

People Things Places Time Experiences Events

  Data   Objects   Relationships and Events

  Objects -- popular in the West.   Relationships and Events – popular in the

East.   Objects and Events – seems to be the new

trend.

  The Web has re-emphasized the importance of every object and event being connected to others -- East Meets West.

  Consider a Web in which each node   Is an event   Has informational as well as experiential data   Is connected to other nodes using

  Referential links   Structural links   Relational links   Causal links

  Explicit links can be created by anybody

  This EventWeb is connected to other Webs.

  SN are web-based services that allow individuals to:   construct a public or semi-public profile within a bounded system,   articulate a list of other users with whom they share a connection, and   view and traverse their list of connections and those made by others

within the system.

  The nature and nomenclature of these connections may vary from site to site.

Professor at University of California, IrvineStudied Electronics and Communications at Indian Institute of Technology, KharagpurLives in Irvine, CaliforniaMarried to Sudha JainKnows English, HindiFrom NagpurBorn on June 8


Node in a SN


Connecting People

My Grandparents R My BFF! OMG!

WSJ May 9, 2011

Massive collection of events. Have been reporting events as micro-blogs

Time

Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?

FROM TWEETS TO REVOLUTIONS

Time

Atomic and Composite Events

Middle 4 Billion

Top 1.5 Billion

Bottom 2 Billion

Middle of the Pyramid (MOP):

Ready, BUT …

Most attention by Technologists – so far.

Not Ready

Every human society should be provided with the first two.

Other stages follow only after that.

Basic

Highest

  Resources   Physical: food, water, goods, …   Informational: Wikipedia, Doctors, …   Transportation   Employment   Spiritual

  Timeliness   Efficiency

Connecting People

And Resources

Aggregation and

Composition

Situation Detection

Alerts

Queries

Information

  All traditional Persistent Web sources   Micro blogs

  Status updates   Tweets   Streams

  Micro Events   All sensors ‘Chirping’   Internet of Things

  People input in any form

  Result of   Exponential growth in connectivity   Sensor Networks

  Evolution of Sharing Culture   Technology for Collective Knowledge

  Each Micro-blog:   What’s on your mind?   What’s happening?   Share What’s New …

  Really an event reported by Humans.   Can associate experiential data along with

information.   Time and location can be associated.

  Billions of disparate kinds of sensors being placed everywhere.

  Each sensor detects ‘basic events’ and broadcasts it in a simple form.

  Develop a system to process these micro-events and make them useful.

  ‘Chirps’ could be of different types   Define behaviors like:

  Heavy traffic   Popular event going on   People leaving X area   Violence starting   . . .

  Use for Macro-behvior analysis

33

Less abstrac*on,

More detail

More abstrac*on,

Less detail

Characteriza*ons

Transforma*ons

Level 1: Unified representa*on (STT Data)

Level 2: Aggrega*on (Emage)

Level 3: Symbolic Rep.

(Events)

Proper*es

Proper*es

Proper*es

Representa*ons

Level 0: Raw data

Examples

Speed at Exit 7

Number of accidents

Average speed, Occupancy rate

Loop sensors

…

e.g. Waze, 511

34

Less abstrac*on,

More detail

More abstrac*on,

Less detail

Characteriza*ons

Transforma*ons

Level 1: Unified representa*on (STT Data)

Level 2: Aggrega*on (Emage)

Level 3: Symbolic Rep.

(Events)

Proper*es

Proper*es

Proper*es

Representa*ons

Level 0: Raw data

Examples

Pollen count in NYC

Badly affected areas

Mean traffic smoke exposure time

Tweets Traffic congestion Pollen counts

Fire reports

Per capita Asthma tweets

  From Micro-behavior to Macro-behavior   Studied in many fields:

  Economics   Thermodynamics   Systems Biology

  Web facilitates this for many novel applications

  Divide space (world) into small Pixels of appropriate size.

  Assume that each event is a particle of a specific type. Create a Social Image for specific type of events.

  A time-ordered sequence of these emages will be similar to a video representing spatio-temporal changes in events of that type.

S. No Operator Input Output 1 Selection σ Temporal

E-‐mage Set Temporal E-‐mage Set

2 Arithmetic & Logical⊕

K*Temporal E-‐mage Set

Temporal E-‐mage Set

3 Aggregation α Temporal E-‐mage set Temporal E-‐mage Set 4 Grouping γ Temporal E-‐mage Set Temporal E-‐mage Set 5 Characterization :

• Spatial φ • Temporal τ

• Temporal E-‐mage Set • Temporal Pixel Set

• Temporal Pixel Set • Temporal Pixel Set

6 Pattern Matching ψ • Spatial φ • Temporal τ

• Temporal E-‐mage Set • Temporal Pixel Set

• Temporal Pixel Set • Temporal Pixel Set

38

  Spatio temporal variation: Event detection

into ‘high’ and ‘low ’activity zones.

Situational controller

• Goal • Macro Situation • Rules

Micro event e.g. “Arrgggh, I

have a sore throat”

(Loc=New York, Date=12/09/10)

Macro situation

Control Action “Please visit nearest CDC

center at 4th St immediately”

Date=12/09/10

Alert Level=High

Level 1 personal threat + Level 3 Macro threat -> Immediate action

1.  For centralized agencies   Most of what we have done so far

2.  For individuals who subscribe   Asthma

3.  Alerts based on (implicit subscription): user’s (FB) interests, events attending, trips, sports, music, fan pages…   Maybe we can derive asthma, from FB details?

4.  I’m bored! What’s around me? (based on a generic interest set)   NowLedger

  Brand monitoring   Epidemic monitoring   Political campaigns   Decision making: e.g. iphone new store

  Asthma   Wildfires   Traffic   Dating   Coupons   …

  Concerts, Campaigns, Memorabilia, Book stores, (anything you are a fan of)

  Your friends   Only show content whose ‘information’ is high.

If your friend normally lives 500 miles away and is NOW within 5 miles then alert. If he is always within 2 miles, don’t alert.

  Food   Drinks   Movies   Concerts   Academic   Professional

Direct the innovation and R&D towards the needs of the World’s middle class – the

Middle of the Pyramid (MOP).

Expand the Middle to cover the Bottom.

Health Education Agriculture Social

For addressing all life elements.

 Resource ingestion  Situation analysis   ‘Real Time’ matching of needs

and availability of resources   Interaction environments  User engagement, … and many

others

  Event Based   Experience Centric   Centered around YOU

  No Country Left Behind

Contact: [email protected]