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PeGOV 2014 – 2nd Workshop on Personalization in eGovernment Services and Applications 
11 July 2014, Aalborg, Denmark 
TweetAlert: 
Semantic Analytics in Social Networks 
for Citizen Opinion Mining 
in the City of the Future 
Julio Villena-Román1,2, 
Adrián Luna-Cobos1,3, José Carlos González-Cristóbal3,1 
1 DAEDALUS - Data, Decisions and Language, S.A. 
2 Universidad Carlos III de Madrid 
3 Universidad Politécnica de Madrid 
jvillena@daedalus.es, aluna@daedalus.es, josecarlos.gonzalez@upm.es
PeGOV-2014 
11 July 2014, Aalborg, Denmark 2 
Agenda 
! Framework 
! Citizen Sensor 
! System 
! Business cases 
! Future work
PeGOV-2014 
11 July 2014, Aalborg, Denmark 3 
Framework 
! Ciudad 2020 aims to achieve significant improvements in areas of 
energetic efficiency, Internet of the Future, Internet of Things, human 
behaviour, environmental sustainability and mobility and transport, in 
order to design the City of the Future: sustainable, efficient, smart. 
! Spanish R&D project, INNPRONTA Programme, Center for Industrial 
Technological Development (CDTI), Ministry of Economy and 
Competitiveness 
! 2011-2014 
! 16,3 M€ budget 
! 5 multinational corporations, 4 SMEs, 8 PRIs 
! Daedalus focuses on the automatic extraction of meaning from all types 
of multimedia content, using NLP technologies and data/text analytics to 
help our customers solve any challenge in these areas.
leisure and free time 
surveys 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 4 
Citizen Sensor 
mobility 
professional activities 
opinions in 
social media 
relationship with 
public administration 
collaborative 
sensing 
relationship with 
other people 
Citizen 2020 = another city sensor
PeGOV-2014 
11 July 2014, Aalborg, Denmark 5 
Citizen Sensor 
! Innovative way to capture a very descriptive high-level 
heterogeneous information, bringing high added value 
especially when considering aggregations 
! More complex and richer information than other sensors 
! “smells awful”, “there is a fire”, “I’m going to the sales”… 
! Individual actions may show citizen trends 
! validate a bus ticket " route density 
! Opinion/sentiments of the citizen about the city 
! follow social networks to assess the impact of new policies 
! Collaborative sensing 
! using smartphones to get data (pollution, energy consumption) with low 
cost and new possibilities
Our approach 
What: Build a system able to capture, store and analyze user 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 6 
messages 
Where: In Twitter 
For whom: City administrators 
What for: To help them rapidly and easily understand citizen 
behaviour trends and know their opinion about city 
services, events, etc. 
Why: To enable them to better understand citizen necessities, 
generate hypotheses over urban behaviour models, in 
order to improve municipal management policies, 
bringing them closer to the actual reality of the citizens 
How: Using NLP technologies 
When: In real-time
PeGOV-2014 
11 July 2014, Aalborg, Denmark 7 
Architecture
Information Repository 
! Stores the high volume of data and provides advanced search 
functionality to exploit the information 
! Based on Elasticsearch 
! open source, distributed, real-time search and analytics engine 
! complex search capabilities 
! scalable high-performance solution 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 8 
http://www.elasticsearch.org
PeGOV-2014 
11 July 2014, Aalborg, Denmark 9 
Gatherer 
! Set of concurrent processes that query the Twitter APIs to collect 
tweets 
! Search or Streaming API 
! Filter by a list of user identifiers, a list of keywords to track (terms, 
hashtags) and/or a set of geographical bounding boxes 
! Returns tweet text, author, location, embedded media 
https://dev.twitter.com/docs/api/1.1
Text 
Classification 
API 
http://textalytics.com 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 10 
Inquirer 
! Set of concurrent processes that annotate tweets using our 
Textalytics Core APIs 
! Entities 
! Concepts 
Topic Extraction API 
! Hashtags 
! Thematic area of the message (transport, economy, daily life…) 
! Citizen Sensor model 
! Alert situations (road accidents, fires, street violence…) 
! Specific location of the user (building, means of transport...) 
! Events to which the text refers (cultural events, sports...) 
! Sentiment polarity : P+, P, NEU, N, N+, NONE 
! Irony and subjectivity 
! User demographics: gender, age, type of tweet author 
Sentiment Analysis API 
User Demographics API
Entities, concepts, hashtags 
Advanced NLP to obtain POS, syntactic tree and semantic analyses of the 
text and use it to identify different types of significant elements 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 11
Text classification 
State-of-the-art hybrid text classification model using a statistical 
classification combined with a rule-based filtering 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 12 
Social Media 
Citizen Sensor
PeGOV-2014 
11 July 2014, Aalborg, Denmark 13 
Topics
PeGOV-2014 
11 July 2014, Aalborg, Denmark 14 
Alerts
PeGOV-2014 
11 July 2014, Aalborg, Denmark 15 
Locations, events
Sentiment analysis 
State-of-the-art lexicon-based model for sentiment analysis, using POS 
and syntactic tree for detecting negation and controlling the scope of 
modifiers + subjectivity classification + irony detection 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 16
User Demographics 
Text classification based on n-grams model to guess user type, gender and 
age from his/her login, name and profile description 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 17
PeGOV-2014 
11 July 2014, Aalborg, Denmark 18 
Example 
{ 
"text":"el viento ha roto una rama y hay un atascazo increible en toda la gran vía...", 
"tag_list":[ 
{"type":"sensor", "value":"011002 Ubicación - Exteriores - Vías públicas"}, 
{"type":"sensor", "value":"070700 Alertas meteorológicas - Viento"}, 
{"type":"sensor", "value":"080100 Incidencia - Congestión de tráfico"}, 
{"type":"topic", "value":"06 medio ambiente, meteorología y energía"}, 
{"type":"entity", "value":"Gran Vía"}, 
{"type":"concept", "value":"viento"}, 
{"type":"sentiment", "value":"N"}, 
{"type":"subjectivity", "value":"OBJ"}, 
{"type":"irony", "value":"NONIRONIC"}, 
{"type":"user_type", "value":"PERSON"}, 
{"type":"user_gender", "value":"FEMALE"}, 
{"type":"user_age", "value":"25-35"} 
] 
}
PeGOV-2014 
11 July 2014, Aalborg, Denmark 19 
Geolocation
PeGOV-2014 
11 July 2014, Aalborg, Denmark 20 
Visualization 
http://www.highcharts.com 
http://openlayers.org 
http://d3js.org
PeGOV-2014 
11 July 2014, Aalborg, Denmark 21 
Ongoing business cases 
! City console for a local administration to analyze in real-time the 
behaviour and topics of interest of the citizens, with two 
components: 
! a private console, internal for the city services, for analytics 
! a public dashboard to engage citizens with their city, displaying 
attractive, summarized, non-confidential information at selected 
public locations (town hall, libraries, museums) or a LED video wall in 
a populous square in downtown 
! Social alert detection system 
! For 112 emergency services, providing early detection of security-related 
issues
For short/mid term future 
! Trending topics geolocation clustering 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 22 
! Analysis at neighbourhood level 
health 
traffic 
jam 
air pollution 
jellyfish 
pollen
For short/mid term future 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 23 
! Analysis of city pace of life
For short/mid term future 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 24 
! Mobility analysis 
! How, when, why people move through the city 
! Route identification (home"work"free time"home) 
! Route changes (due to weather)
For short/mid term future 
! City reputation and brand personality 
! Automated satisfaction surveys 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 25
This work has been supported by several Spanish R&D projects: Ciudad2020: Hacia un nuevo modelo de ciudad inteligente 
sostenible (INNPRONTA IPT-20111006), MA2VICMR: Improving the access, analysis and visibility of the multilingual and 
multimedia information in web for the Region of Madrid (S2009/TIC-1542) and MULTIMEDICA: Multilingual Information 
Extraction in Health domain and application to scientific and informative documents (TIN2010-20644-C03-01). Authors 
would like to thank all partners for their knowledge and support. 
PeGOV-2014 
11 July 2014, Aalborg, Denmark 26

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Tweet alert - semantic analysis in social networks for citizen opinion mining

  • 1. PeGOV 2014 – 2nd Workshop on Personalization in eGovernment Services and Applications 11 July 2014, Aalborg, Denmark TweetAlert: Semantic Analytics in Social Networks for Citizen Opinion Mining in the City of the Future Julio Villena-Román1,2, Adrián Luna-Cobos1,3, José Carlos González-Cristóbal3,1 1 DAEDALUS - Data, Decisions and Language, S.A. 2 Universidad Carlos III de Madrid 3 Universidad Politécnica de Madrid jvillena@daedalus.es, aluna@daedalus.es, josecarlos.gonzalez@upm.es
  • 2. PeGOV-2014 11 July 2014, Aalborg, Denmark 2 Agenda ! Framework ! Citizen Sensor ! System ! Business cases ! Future work
  • 3. PeGOV-2014 11 July 2014, Aalborg, Denmark 3 Framework ! Ciudad 2020 aims to achieve significant improvements in areas of energetic efficiency, Internet of the Future, Internet of Things, human behaviour, environmental sustainability and mobility and transport, in order to design the City of the Future: sustainable, efficient, smart. ! Spanish R&D project, INNPRONTA Programme, Center for Industrial Technological Development (CDTI), Ministry of Economy and Competitiveness ! 2011-2014 ! 16,3 M€ budget ! 5 multinational corporations, 4 SMEs, 8 PRIs ! Daedalus focuses on the automatic extraction of meaning from all types of multimedia content, using NLP technologies and data/text analytics to help our customers solve any challenge in these areas.
  • 4. leisure and free time surveys PeGOV-2014 11 July 2014, Aalborg, Denmark 4 Citizen Sensor mobility professional activities opinions in social media relationship with public administration collaborative sensing relationship with other people Citizen 2020 = another city sensor
  • 5. PeGOV-2014 11 July 2014, Aalborg, Denmark 5 Citizen Sensor ! Innovative way to capture a very descriptive high-level heterogeneous information, bringing high added value especially when considering aggregations ! More complex and richer information than other sensors ! “smells awful”, “there is a fire”, “I’m going to the sales”… ! Individual actions may show citizen trends ! validate a bus ticket " route density ! Opinion/sentiments of the citizen about the city ! follow social networks to assess the impact of new policies ! Collaborative sensing ! using smartphones to get data (pollution, energy consumption) with low cost and new possibilities
  • 6. Our approach What: Build a system able to capture, store and analyze user PeGOV-2014 11 July 2014, Aalborg, Denmark 6 messages Where: In Twitter For whom: City administrators What for: To help them rapidly and easily understand citizen behaviour trends and know their opinion about city services, events, etc. Why: To enable them to better understand citizen necessities, generate hypotheses over urban behaviour models, in order to improve municipal management policies, bringing them closer to the actual reality of the citizens How: Using NLP technologies When: In real-time
  • 7. PeGOV-2014 11 July 2014, Aalborg, Denmark 7 Architecture
  • 8. Information Repository ! Stores the high volume of data and provides advanced search functionality to exploit the information ! Based on Elasticsearch ! open source, distributed, real-time search and analytics engine ! complex search capabilities ! scalable high-performance solution PeGOV-2014 11 July 2014, Aalborg, Denmark 8 http://www.elasticsearch.org
  • 9. PeGOV-2014 11 July 2014, Aalborg, Denmark 9 Gatherer ! Set of concurrent processes that query the Twitter APIs to collect tweets ! Search or Streaming API ! Filter by a list of user identifiers, a list of keywords to track (terms, hashtags) and/or a set of geographical bounding boxes ! Returns tweet text, author, location, embedded media https://dev.twitter.com/docs/api/1.1
  • 10. Text Classification API http://textalytics.com PeGOV-2014 11 July 2014, Aalborg, Denmark 10 Inquirer ! Set of concurrent processes that annotate tweets using our Textalytics Core APIs ! Entities ! Concepts Topic Extraction API ! Hashtags ! Thematic area of the message (transport, economy, daily life…) ! Citizen Sensor model ! Alert situations (road accidents, fires, street violence…) ! Specific location of the user (building, means of transport...) ! Events to which the text refers (cultural events, sports...) ! Sentiment polarity : P+, P, NEU, N, N+, NONE ! Irony and subjectivity ! User demographics: gender, age, type of tweet author Sentiment Analysis API User Demographics API
  • 11. Entities, concepts, hashtags Advanced NLP to obtain POS, syntactic tree and semantic analyses of the text and use it to identify different types of significant elements PeGOV-2014 11 July 2014, Aalborg, Denmark 11
  • 12. Text classification State-of-the-art hybrid text classification model using a statistical classification combined with a rule-based filtering PeGOV-2014 11 July 2014, Aalborg, Denmark 12 Social Media Citizen Sensor
  • 13. PeGOV-2014 11 July 2014, Aalborg, Denmark 13 Topics
  • 14. PeGOV-2014 11 July 2014, Aalborg, Denmark 14 Alerts
  • 15. PeGOV-2014 11 July 2014, Aalborg, Denmark 15 Locations, events
  • 16. Sentiment analysis State-of-the-art lexicon-based model for sentiment analysis, using POS and syntactic tree for detecting negation and controlling the scope of modifiers + subjectivity classification + irony detection PeGOV-2014 11 July 2014, Aalborg, Denmark 16
  • 17. User Demographics Text classification based on n-grams model to guess user type, gender and age from his/her login, name and profile description PeGOV-2014 11 July 2014, Aalborg, Denmark 17
  • 18. PeGOV-2014 11 July 2014, Aalborg, Denmark 18 Example { "text":"el viento ha roto una rama y hay un atascazo increible en toda la gran vía...", "tag_list":[ {"type":"sensor", "value":"011002 Ubicación - Exteriores - Vías públicas"}, {"type":"sensor", "value":"070700 Alertas meteorológicas - Viento"}, {"type":"sensor", "value":"080100 Incidencia - Congestión de tráfico"}, {"type":"topic", "value":"06 medio ambiente, meteorología y energía"}, {"type":"entity", "value":"Gran Vía"}, {"type":"concept", "value":"viento"}, {"type":"sentiment", "value":"N"}, {"type":"subjectivity", "value":"OBJ"}, {"type":"irony", "value":"NONIRONIC"}, {"type":"user_type", "value":"PERSON"}, {"type":"user_gender", "value":"FEMALE"}, {"type":"user_age", "value":"25-35"} ] }
  • 19. PeGOV-2014 11 July 2014, Aalborg, Denmark 19 Geolocation
  • 20. PeGOV-2014 11 July 2014, Aalborg, Denmark 20 Visualization http://www.highcharts.com http://openlayers.org http://d3js.org
  • 21. PeGOV-2014 11 July 2014, Aalborg, Denmark 21 Ongoing business cases ! City console for a local administration to analyze in real-time the behaviour and topics of interest of the citizens, with two components: ! a private console, internal for the city services, for analytics ! a public dashboard to engage citizens with their city, displaying attractive, summarized, non-confidential information at selected public locations (town hall, libraries, museums) or a LED video wall in a populous square in downtown ! Social alert detection system ! For 112 emergency services, providing early detection of security-related issues
  • 22. For short/mid term future ! Trending topics geolocation clustering PeGOV-2014 11 July 2014, Aalborg, Denmark 22 ! Analysis at neighbourhood level health traffic jam air pollution jellyfish pollen
  • 23. For short/mid term future PeGOV-2014 11 July 2014, Aalborg, Denmark 23 ! Analysis of city pace of life
  • 24. For short/mid term future PeGOV-2014 11 July 2014, Aalborg, Denmark 24 ! Mobility analysis ! How, when, why people move through the city ! Route identification (home"work"free time"home) ! Route changes (due to weather)
  • 25. For short/mid term future ! City reputation and brand personality ! Automated satisfaction surveys PeGOV-2014 11 July 2014, Aalborg, Denmark 25
  • 26. This work has been supported by several Spanish R&D projects: Ciudad2020: Hacia un nuevo modelo de ciudad inteligente sostenible (INNPRONTA IPT-20111006), MA2VICMR: Improving the access, analysis and visibility of the multilingual and multimedia information in web for the Region of Madrid (S2009/TIC-1542) and MULTIMEDICA: Multilingual Information Extraction in Health domain and application to scientific and informative documents (TIN2010-20644-C03-01). Authors would like to thank all partners for their knowledge and support. PeGOV-2014 11 July 2014, Aalborg, Denmark 26