Big Data and Social Data

Mining

Fosca Giannotti KDDLAB

http://kdd.isti.cnr.it

Università di Pisa & ISTI-CNR, Italy

BIG Data

10 July 2013

Shopping patterns & lifestyle

Desires, opinions, sentiments

Relationships & social ties

Movements

Big data “proxies” of social life

GPS: detailed movements within an

area

Social Networks: goal of the

movement

23 luglio 2013 Analisi di Reti Sociali. Aprile-Maggio 2011

10

Big data & new

questions to ask

Google Flu Trends

Nature 457, 1012-1014 (2009)

where-is-the-happiest-city-in-the-usa?

Social mining is about

• discovering patterns and models of human

behaviour across the various social

dimensions that have big data "proxies"

nowadays :

–desires and opinions,

– relationships and social ties,

– life-styles

– mobility

BIG DATA

as a proxy

of human mobility

A12 Sud

Cascina

Marina di Pisa/TirreniaLucca

Understanding city access paths

Understanding city access paths

Discovering individual systematic movements

Work-Home

Home-Work

Using the profiles to classify the incoming flows

Mobility profile matching

Mobility

Profile

Mobility

Profile

Spatio Temporal

Routing matchesUser A (as driver) User B (as passenger)

A can serve most of the routines of B � the match is suggested.

Understanding car pooling impact

?

Community

=

Suggestion

=

Actual Network

Matching Network

Mobility Atlas of a town

Analyze individual call habits from

GSM data to recognize profiles

–Resident

–Commuters

–Visitors/Tourists

Call Habit Profile Construction

Users’ call

habit

profile

Week: working days &

weekend

0:00-7:59

8:00-18:59

19:00-23:59

Resident profile classification

Resident profile

Commuter profile classification

Resident profile

Commuter profile

Visitor profile classification

Resident profile

Commuter profile

Visitor profile

Night visitors

Daylight visitors

Urban Sociometer

Resident profile

Commuter profile

Visitor profile

Among the unclassified there are other

interesting profiles:

- The occasional visitors;

- The «night visitors».

Discover the borders of mobility

Salvatore Rinzivillo, Mainardi, Pezzoni, Michele Coscia, Dino Pedreschi, Fosca Giannotti:

Discovering the Geographical Borders of Human Mobility. KI 26(3): 253-260 (2012)

Mirco Nanni, Roberto Trasarti, et al.:

MP4-A Project: Mobility Planning for Africa. “Data for Development” Orange challenge, 2013

Mirco Nanni, Roberto Trasarti, et al.:

MP4-A Project: Mobility Planning for Africa. “Data for Development” Orange challenge, 2013

Data scientist,

the sexiest job of 21st century• … a new kind of

professional has

emerged, the data

scientist, who combines

the skills of software

programmer, statistician

and storyteller/artist to

extract the nuggets of

gold hidden under

mountains of data.

Knowledge Discovery & Data Mining Laboratory | kdd.isti.cnr.it