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Inteligência ColetivaInteligência Coletiva
Thiago H Silva
2
Collective Intelligence
Thiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG
?
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Nowadays
Thiago H. Silva – DCC/UFMG
- Smartphones are extremelly popular
- Mobile data plans as well
Thiago H. Silva – DCC/UFMG
Many sensors
4
Nowadays
Thiago H. Silva – DCC/UFMG
- Smartphones are extremelly popular
- Mobile data plans as well
Thiago H. Silva – DCC/UFMG
Traffic monitoring Photo sharing Location sharing
Many sensors
Humans in the sensing process
Thiago H. Silva – DCC/UFMG
Collective Intelligence
Humans in the sensing process
Thiago H. Silva – DCC/UFMG
Collective Intelligence
Humans in the sensing process
Thiago H. Silva – DCC/UFMG
Collective Intelligence
Social sensors
Humans in the sensing processCollective Intelligence
Social sensors
Humans in the sensing process
Thiago H. Silva – DCC/UFMG
Collective Intelligence
Collective Intelligence
10
Collective Intelligence
Thiago H. Silva – DCC/UFMG
11
Collective Intelligence
Thiago H. Silva – DCC/UFMG
T1 T2 T3
Graph to study trajectories
Collective Intelligence
Thiago H. Silva – DCC/UFMG
T1 T2 T3
Can we those data to help large scale study of urban societies ?
13DCC/UFMGThiago H. Silva – DCC/UFMG
City Image
Revealing the City that We Cannot See.Thiago Silva, Pedro Vaz de Melo, Jussara Almeida, Juliana Salles, Antonio Loureiro. ACM Transactions on Internet Technology. 2014.
UFMG Microsoft Research
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City Image
Belo Horizonte, Brazil New York, USA
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City Image
Thiago H. Silva – DCC/UFMG
Belo Horizonte, Brazil New York, USA
School
Nightclub
Typical Monday
Bar
WorkRestaurant
Are transitions random?
City Image
Thiago H. Silva – DCC/UFMG
Belo Horizonte, Brazil New York, USA
School
Nightclub
Typical Monday
Bar
WorkRestaurant
There are more favorable transitions than others
City Image
DCC/UFMG
Transition graph: check-in accordingly to routines or local preference
Pizza place“Food”
User1Time 1
Thiago H. Silva – DCC/UFMG
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City Image
DCC/UFMG
Transition graph: check-in accordingly to routines or local preference
Jazz bar“Nightlife”
User1Time 2
Pizza place“Food”
User1Time 1
Thiago H. Silva – DCC/UFMG
City Image
DCC/UFMG
Transition graph: check-in accordingly to routines or local preference
Food Nightlife
Transition user 1
Jazz bar“Nightlife”
User1Time 2
Pizza place“Food”
User1Time 1
Thiago H. Silva – DCC/UFMG
Transition graphNodes are main categories of places
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City Image
DCC/UFMGThiago H. Silva – DCC/UFMG
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City Image
Thiago H. Silva – DCC/UFMG
Cur
rent
loca
tion
Next location
Cur
rent
loca
tion
Next location
RejectionRejectionIndiferenceIndiference FavoringFavoring
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City Image
Thiago H. Silva – DCC/UFMG
Cur
rent
loca
tion
Next location
Cur
rent
loca
tion
Next location
Invisible images
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City Image
Thiago H. Silva – DCC/UFMG
Cur
rent
loca
tion
Next location
Cur
rent
loca
tion
Next location
24DCC/UFMG
Cultural Diferences
Thiago H. Silva – DCC/UFMG
You are What you Eat (and Drink): Identifying Cultural Boundaries by Analyzing Food & Drink Habits in Foursquare.Thiago Silva, Pedro Vaz de Melo, Jussara Almeida, Mirco Musolesi, Antonio Loureiro. ICWSM'14
UFMG UCL
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Cultural diferences
DCC/UFMGThiago H. Silva – DCC/UFMG
Big challenge: find appropriate data to use
Traditional methods: surveys – Expensive– Hard to detect dynamic changes
We propose to extract this elements from social media
Cultural diferences
DCC/UFMGThiago H. Silva – DCC/UFMG
Eating & drinking habits are fundamental elements in a culture
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Cultural diferences
DCC/UFMGThiago H. Silva – DCC/UFMG
Eating and drinking habits are fundamental elements in a culture
Map each user in
Cultural diferences
DCC/UFMGThiago H. Silva – DCC/UFMG
Eating and drinking habits are fundamental elements in a culture
Map each user in
Like questions in a Survey!
Cultural diferences
DCC/UFMGThiago H. Silva – DCC/UFMG
Eating and drinking habits are fundamental elements in a culture
Map each user in
represents if user likes Users answers
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Cultural analysis of individuals
DCC/UFMGThiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG 30
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Extraction of cultural signatures
DCC/UFMG
Spatial evaluation
Thiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG 31
Results for cities
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Extraction of cultural signatures
DCC/UFMG
Spatial evaluation
Thiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG 32
Brazil
USA
Indonesia
Japan
Results for cities
33
Extraction of cultural signatures
DCC/UFMGThiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG
Temporal evaluation
33
Weekdays
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Identifying cultural boundaries
DCC/UFMGThiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG 34
Each color/symbol indicates a cluster
Clustering areas inside cities
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Identifying cultural boundaries
DCC/UFMGThiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG 35
London regions
Tokyo regions
NYC regions
Clustering areas inside cities
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Identifying cultural boundaries
DCC/UFMGThiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG 36
Comparing with World Value Survey data
The similarities are striking!
You are What you Eat (and Drink): Identifying Cultural Boundaries by Analyzing Food & Drink Habits in Foursquare.Thiago Silva, Pedro Vaz de Melo, Jussara Almeida, Mirco Musolesi, Antonio Loureiro. ICWSM'14
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Take away message
DCC/UFMGThiago H. Silva – DCC/UFMGThiago H. Silva – DCC/UFMG 37
There many opportunities to explore collective intelligence for innovation!
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Thanks!
Thiago H. Silva – DCC/UFMG
Thanks!Obrigado!
www.dainf.ct.utfpr.edu.br/~thiagohs
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