A framework for Semantic Content Analysis in the context of L'Aquila Social Urban Network

Smart Cities AI*IA 2013 - 1st Workshop on Artiﬁcial Intelligence for Smart Cities

Torino (Italy) - 05.12.2013

Cataldo Musto, Giovanni Semeraro, Pasquale Lops, Marco de Gemmis, Fedelucio Narducci,
Mauro Annunziato, Luciana Bordoni, Claudia Meloni, Franco F.Orsucci, Giulia Paoloni

A framework for semantic content
analysis in the context of
l’Aquila Social Urban Network

April, 6
2009
C. Musto, G. Semeraro, P. Lops, M. de Gemmis, F. Narducci, M. Annunziato, L. Bordoni, C. Meloni, F. F. Orsucci, G.Paoloni
A framework for semantic content analysis in the context of L’Aquila Social Urban Nework
AI*IA Smart Cities 2013 - Torino, Italy - 05.12.2012

3:32 am

5.8

magnitude
earthquake


almost 20 billions damages

70,000 people displaced

309 people died

...4 years later.

a little ﬂashback


September 29, 2009 :-)


November 18, 2009 :-)


November 18, 2009 :-)
October 7, 2010 :-)


November 18, 2009 :-)
October 7, 2010 :-)
October 25, 2010 :-(


November 18, 2009 :-)
October 7, 2010 :-)
October 25, 2010 :-(
June 6, 2012 :-(

what is really going on in L’Aquila?


22,000 people still displaced

7 billion fundings still missing

several buildings still ruined

19 new towns spread around L’Aquila

15 km

19 new towns spread around L’Aquila

15,200 people living in the ‘new towns’

diaspora

what about the consequences?


loss of sense of belonging

loss of sense of trust

loss of relationships

one word: loss of social capital

the current situation makes L’Aquila a
perfect work bench for
smart cities-related initiatives

“A city can be deﬁned as ‘smart’ when investments in human
and social capital fuel sustainable economic development and a
high quality of life” (Caragliu et al, 2009)

“A city can be deﬁned as ‘smart’ when investments in human
and social capital fuel sustainable economic development
and a high quality of life” (Caragliu et al, 2009)

European Community already deﬁned six axes
to evaluate ‘city smartness’

Several research projects already paid serious attention towards
processes able to improve people’s qualify of life

Project “City 2.0”

Goal: development of a smart town model


2011-2014
3.5M euro


Smart Lightning


Smart Mobility and Smart Environment


our contribution to ‘City 2.0’
Smart Communities


Smart Communities
small proof-of-concept in L’Aquila

Smart
Ring


Smart Communities
goal: to revitalize social capital and urban heritage of L’Aquila


insight: collective intelligence


collective intelligence
“a shared or group intelligence that emerges from the
collaboration and competitions of many individuals”


Smart Participation / Smart Communities
sustainable development also refers to the quality of life itself, including
the development of social participation, a key element to advance a
“sense of community” - (M.Annunziato, ENEA)


L’Aquila Social Urban Network (SUN)


Social Urban Network

• Hybrid City Model developed by ENEA
• Synergy between ICTs and real world
• Use of social networks to foster relationships
and communication between people

•
•
•

Deep content analytics
Extraction of social indicators scores
Initiatives activated by community promoters


SUN architecture


Smart Node

Meeting place for sharing and consuming
information about L’Aquila

Smart Node

a bridge between
virtual communities and real world

Semantic Content Analyzer
the focus of this presentation


architecture


architecture
Input
Facebook Pages,
Twitter or Google
Plus accounts,
Pinterest boards.
=
Social Content


architecture
Step 1
Social Extractor
extracts
information about
L’Aquila from the
social web
A database of
community
contributions is
created

Social Extractor (step 1/5)
scenario


architecture
Step 1
Social Extactor
extracts
information about
L’Aquila from the
social web
A database of
community
contributions is
created

architecture

Step 2
Community
contributions are
semantically
annotated through
a pipeline of
semantic taggers
Contributions
enriched with
high-level
concepts are
stored again


Semantic Tagger (step 2/5)
scenario

output: alloggi, ricostruzione, ediﬁci, memoria_storica

Semantic Tagger (step 2/5)
scenario

output: terremoto, terrore, paura

architecture

Step 3
A sentiment
analysis algorithm
assigns a polarity
(negative, positive,
neutral) to each
social content
Contributions
enriched with the
sentiment the
convey are stored
again


architecture

Step 3
A sentiment
analysis algorithm
assigns a polarity
(negative, positive,
neutral) to each
social content
Contributions
enriched with the
sentiment they
convey are stored
again


Sentiment Analyzer (step 3/5)
scenario

+++++ :-)

Sentiment Analyzer (step 3/5)
scenario

------ :-(

architecture

Step 4
Each social content
(with its polarity) is
classiﬁed wrt the
social indicator it
refers to
The score for the
indicator is the sum
of the polarity of
the social content
referring to it


social indicators (again)

the polarity of each social content inﬂuences the
score of the indicator it refers to

Social Capital Mapper (step 4/5)
scenario

+

+


Social Capital Mapper (step 4/5)
scenario

:-(

architecture

Step 5
Given a score for
each social
indicator, the
community
promoter proposes
initiatives aimed at
improving or
recovering the
social capital of
L’Aquila


Community Promoter (step 5/5)
scenario
community
promoter

social
indicators
monitoring
tool

initiatives


Recap

• Collective intelligence-based approach
• Social content are analyzed to extract latent

information about the social capital of L’Aquila

•
•

Pipeline of semantic taggers and sentiment
analysis algorithms

Social indicators scores are exploited by
community promoters to empower social
capital of the city


“data is the new oil” (IBM)


questions?
Cataldo Musto, Ph.D

SWAP Research Group, Università degli Studi di Bari
cataldo.musto@uniba.it

A framework for Semantic Content Analysis in the context of L'Aquila Social Urban Network

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