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

A framework for semantic content analysis in the context of

l’Aquila Social Urban Network

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

April, 6 2009

C. Musto, G. Semeraro, P. Lops, M. de Gemmis, F. Narducci, M. Annunziato, L. Bordoni, C. Meloni, F. F. Orsucci, G.PaoloniA 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

5.8magnitudeearthquake



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


19 new towns spread around L’Aquila

15 km


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”


Project “City 2.0”Goal: development of a smart town model


Project “City 2.0”

2011-20143.5M euro


Project “City 2.0”Smart Lightning


Project “City 2.0”Smart Mobility and Smart Environment


our contribution to ‘City 2.0’Smart Communities


Smart Communitiessmall proof-of-concept in L’Aquila

Smart Ring


Smart Communitiesgoal: 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”


Project “City 2.0”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)

• 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


Project “City 2.0”Social Urban Network


Project “City 2.0”SUN architecture


Project “City 2.0”Smart Node

Meeting place for sharing and consuming information about L’Aquila


Project “City 2.0”Smart Node

a bridge between virtual communities and real world


Semantic Content Analyzerthe focus of this presentation


Semantic Content Analyzerarchitecture



InputFacebook Pages,

Twitter or Google Plus accounts,

Pinterest boards.=

Social Content



Step 1Social Extractor

extracts information about L’Aquila from the

social web

A database of community

contributions is created


Social Extractor (step 1/5)scenario



Step 1Social Extactor

extracts information about L’Aquila from the

social web

A database of community

contributions is created


Semantic Content Analyzerarchitecture Step 2

Community contributions are

semantically annotated through

a pipeline of semantic taggers

Contributions enriched with

high-level concepts are stored again



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



A sentiment analysis algorithm assigns a polarity (negative, positive, neutral) to each social content

Contributions enriched with the

sentiment the convey are stored

again



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

------ :-(



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



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

+ +


scenario

:-(

Social Capital Mapper (step 4/5)



Step 5Given 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

• 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


Semantic Content AnalyzerRecap


“data is the new oil” (IBM)

questions?Cataldo Musto, Ph.D

SWAP Research Group, Università degli Studi di [email protected]


mailto:[email protected]

mailto:[email protected]

Technology

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