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Listening to the pulse of our cities fusing Social Media Streams and Call Data Records

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The digital reflection of our cities is sharpening and it is tracking their evolution with a decreasing delay. This happens thanks to the pervasive deployment of sensors, the wide adoption of smart phones, the usage of (location-based) social networks and the availability of datasets about urban environment. So while data becomes every day more abundant, decision makers face the challenge to increase their capability to create value out of the analysis of this data. This key note presents how advance visual analytics, ontology base data access and information flow processing methods can help in making sense of Social Media Streams and Call Data Records from Mobile Network Operators during city scale events. Real-world deployments demonstrate the ability of those methods to advance our ability to feel the pulse of our cities in order to deliver innovative services.

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Listening to the pulse of our cities fusing Social Media Streams and Call Data Records

  1. 1. Listening to the pulse of our cities fusing Social Media Streams and Call Data Records Emanuele Della Valle emanuele.dellavalle@polimi.it http://emanueledellavalle.org 18th International Conference on Business Information Systems 24-26 June 2015, Poznań, Poland
  2. 2. http://emanueledellavalle.org - Emanuele Della Valle Me  Assistant Professor at DEIB Politecnico di Milano  Expert in semantic technologies and stream computing  Inventor of stream reasoning: an approach to master the velocity and variety dimension of Big Data  15 years experience in research and innovation projects  startupper: fluxedo.com 3 Emanuele Della Valle http://emanueledellavalle.
  3. 3. http://emanueledellavalle.org - Emanuele Della Valle Acknowledgements  Politecnico di Milano • DEIB – What - Scientific direction - Semantic technologies - Stream Processing - Data science – Who - Emanuele Della Valle - Marco Balduini • Density Design Lab – What - Visual analytics – Who - Paolo Ciuccarelli - Matteo Azzi  Telecom Italia • SKIL Lab – What - Big Data technology - Data Science – Who - Fabrizio Antonelli - Roberto Larker  Funding agency 4
  4. 4. http://emanueledellavalle.org - Emanuele Della Valle Agenda  Context  Problem  Experimental setting  Solution  Evaluation  Conclusions 5
  5. 5. http://emanueledellavalle.org - Emanuele Della Valle The digital reflection of our cities is sharpening 6 [photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg]
  6. 6. http://emanueledellavalle.org - Emanuele Della Valle The digital reflection of our cities is sharpening 7 [photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg] because the urban environment is captured in open datasets
  7. 7. http://emanueledellavalle.org - Emanuele Della Valle The digital reflection of our cities is sharpening 8 [photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg] and streams of information flows through our cities thanks to
  8. 8. http://emanueledellavalle.org - Emanuele Della Valle The digital reflection of our cities is sharpening 9 [photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg] and streams of information flows through our cities thanks to the pervasive deployment of sensors
  9. 9. http://emanueledellavalle.org - Emanuele Della Valle The digital reflection of our cities is sharpening 10 [photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg] and streams of information flows through our cities thanks to the wide adoption of smart phones
  10. 10. http://emanueledellavalle.org - Emanuele Della Valle The digital reflection of our cities is sharpening 11 [photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg] and streams of information flows through our cities thanks to the usage of (location-based) social networks
  11. 11. http://emanueledellavalle.org - Emanuele Della Valle and it is tracking changes with a decreasing delay 12
  12. 12. http://emanueledellavalle.org - Emanuele Della Valle and it is tracking changes with a decreasing delay 13 Data source By when Frequency Delay Census data 100s year years months Newspaper 100s year days 1 day Weather sensors 10s year hours/minutes hours/minutes TV news 10s years hours minutes Traffic sensors years 15 minutes minutes Call Data Recors years 15 minutes hours Social media years seconds seconds IoT recently milliseconds milliseconds
  13. 13. http://emanueledellavalle.org - Emanuele Della Valle 14 Data pile up without making decision any easier I have to decide: A or B? Why not C? What if D? mayor
  14. 14. http://emanueledellavalle.org - Emanuele Della Valle But smarter Big Data can … …advance our ability to feel the pulse of our cities 15 fusing all those data sources making sense of the fused information mayor Definitely E! to improve decision making and deliver innovative services
  15. 15. http://emanueledellavalle.org - Emanuele Della Valle Can we collect, analyse and repurpose • social media and • Call Data Records to allow • perceiving emerging patterns and • observing their dynamics? Let's focus on a concrete research question 16 [photo: https://www.flickr.com/photos/debord/4932655275]
  16. 16. http://emanueledellavalle.org - Emanuele Della Valle Can we collect, analyse and repurpose • social media captured at place and events and • privacy-preserving aggregates of Call Data Records to allow visually • perceiving emerging patterns and • observing their dynamics? More precisely, the research question is 17 [photo: https://www.flickr.com/photos/debord/4932655275]
  17. 17. http://emanueledellavalle.org - Emanuele Della Valle How to set up an experiment? 18 [photo: https://www.flickr.com/photos/myfuturedotcom/6053042920] Question Answer Which city? Milan Comparing what? Milan Design Week vs. Milan in general Experimental subjects? Event Managers & casual audience
  18. 18. http://emanueledellavalle.org - Emanuele Della Valle What's Milan Design Week? 19 [map: http://www.fuorisalone.it] The Milan Design Week (MDW) is a city-scale event • held yearly in Milan, • featuring around 1,200 events • in 500+ places spread across the city and • attracting about half a million people from all over the world.
  19. 19. http://emanueledellavalle.org - Emanuele Della Valle Ingredients of the proposed solution  Big Data technologies - Address "velocity" of data streams in memory - Address "volume" of data that do not fit in memory  semantic technologies - Address "variety" using Ontology Based Data Access - Named Entity Recognition and Linking  data science - Statistical modelling - detecting anomalies  Visual analytics - Allow no-expert access to data - Tell stories out of data 20
  20. 20. http://emanueledellavalle.org - Emanuele Della Valle 21 CitySensing - a solution for event managers (2013) F. Antonelli, M.Azzi, M.Balduini, P.Ciuccarelli, E.Della Valle, R. Larcher: City sensing: visualising mobile and social data about a city scale event. AVI 2014: 337-338 http://jol.telecomitalia.com/jols kil/citysensing/
  21. 21. http://emanueledellavalle.org - Emanuele Della Valle 22 CitySensing - a solution for casual audience (2014) M.Balduini, E.Della Valle, M.Azzi, R.Larcher, F.Antonelli, and P.Ciuccarelli: CitySensing: Fusing City Data for Visual Storytelling. IEEE MultiMedia. TO APPEAR http://jol.telecomitalia.com/jolskil/citysensing/ http://citysensing.fuorisalone.it/
  22. 22. http://emanueledellavalle.org - Emanuele Della Valle 23 How CitySensing works – step 0 Set up a conceptual model (FraPPE) to master the variety in the data sources M.Balduini, E. Della Valle: FraPPE: a vocabulary to represent heterogeneous spatio-temporal data to support visual analytics. ISWC 2015 TO APPEAR
  23. 23. http://emanueledellavalle.org - Emanuele Della Valle How CitySensing works – step 0  FraPPE • Goal: a vocabulary to represent heterogeneous spatio- temporal data to support visual analytics  FraPPE offers an homogenous view to the visual analytics interface built on heterogeneous data 24
  24. 24. http://emanueledellavalle.org - Emanuele Della Valle How CitySensing works – step 1 25 For every pixel compute the volume of Call Data Records (using privacy-preserving aggregation) Real data recorded on 13 April 2013 between 13:00 and 00:00
  25. 25. http://emanueledellavalle.org - Emanuele Della Valle How CitySensing works – step 2 26 Find the anomalous pixels comparing the current volumes with a model of the volumes in this time period Real data recorded on 13 April 2013 between 13:00 and 00:00
  26. 26. http://emanueledellavalle.org - Emanuele Della Valle How CitySensing works – step 3 27 Map anomalies to the districts of Milano Design Week Brera Tortona What's this? Real data recorded on 13 April 2013 between 13:00 and 00:00
  27. 27. http://emanueledellavalle.org - Emanuele Della Valle How CitySensing works – step 4 28 For every anomalous pixel capture the hashtags and semantic entities named in the social media streams Brera Tortona What's this? Real data recorded on 13 April 2013 between 13:00 and 00:00
  28. 28. http://emanueledellavalle.org - Emanuele Della Valle How CitySensing works – step 5 29 Take away the hashtags and semantic entities that are systematically used Brera Tortona Real data recorded on 13 April 2013 between 13:00 and 00:00
  29. 29. http://emanueledellavalle.org - Emanuele Della Valle 30 Logical architecture of CitySensing – setup time Analyse Data Stream Build Models Capture Data Stream Capture Static Data MDW
  30. 30. http://emanueledellavalle.org - Emanuele Della Valle 31 Logical architecture of CitySensing – run time Analyse Data Stream Build Models Detect Anomalies Capture Data Stream Visualize Analysis Store Analysis Capture Static Data MDW
  31. 31. http://emanueledellavalle.org - Emanuele Della Valle Capturing static data via FraPPE  The frame duration was fixed to 15 minutes  Milano area was covered with • 1 grid (100x100) • 10,000 cells • 250x250 meters in each cell (the size of the mobile network cells in the centre of Milan)  During the Milano Design Week a total of 5.76 Mln pixel were captured  +1000 events in +600 places where collected using the crowd-sourced databases of fuorisalone.it, breradesigndistrict.it and tortonaroundesign.com thanks to a partnership with studiolabo 32 Cells in which there are places hosting Milan Design Week 2013 events
  32. 32. http://emanueledellavalle.org - Emanuele Della Valle Processing Telecom Italia Call Data Records  1.92 Mln Gaussian models were built • one for each pixel (i.e., for each frame and cell) • grouping the frames by working and week-end days • using two months of Call Data Records, and • verifying volume of CDR has a Gaussian distribution with an Anderson-Darling test with a significance of 0.05  Built on Pig, R e Cascalog  The processing on 7 m1.large EC2 machines took 24 hours 33 Bad case Good case Histogram Histogram Q-QPlot Q-Qplot
  33. 33. http://emanueledellavalle.org - Emanuele Della Valle Processing Telecom Italia Call Data Records  Volume of CDR captured in Milan during the Design Week  Calls, SMS and Internet access were aggregated (with privacy-preserving methods) and an anomaly index was computed for each of the 5.76 Mln pixel  The processing of 1 day on 7 m1.large EC2 took 20 mins 34 What 2013 2014 Calls 16,743,875 19,719,629 SMSs 19,454,497 20,240,485 Internet data accesses 137,381,761 197,767,245 [image: https://cerijayne.files.wordpress.com/2011/10/outliersss.png]
  34. 34. http://emanueledellavalle.org - Emanuele Della Valle Do CDR-anomalous pixels relate to events?  CDR-anomalous pixels =pixels in which the anomaly index is high (>+2σ and <-2σ)  To test if the anomalous pixels were related to the events of the Milan Design Week • We used three ground truth – the pixel of Milan – the pixels of Brera district – the pixels of Tortona district where there was at least an event of Milan Design Week 2013 • We compute – Precision – Recall of the anomalous pixels to find pixels in those three ground truths 35
  35. 35. http://emanueledellavalle.org - Emanuele Della Valle 36 Do CDR-anomalous pixels relate to events? 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 MilanBreraTorotna 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 Tuesday Wednesday Thursday Friday Saturday Sunday precision
  36. 36. http://emanueledellavalle.org - Emanuele Della Valle 37 Do CDR-anomalous pixels relate to events? 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 MilanBreraTorotna 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 Tuesday Wednesday Thursday Friday Saturday Sunday recall
  37. 37. http://emanueledellavalle.org - Emanuele Della Valle 38 Do CDR-anomalous pixels relate to events? 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 MilanBreraTorotna 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 Tuesday Wednesday Thursday Friday Saturday Sunday precision recall
  38. 38. http://emanueledellavalle.org - Emanuele Della Valle Processing Social Streams  The machinery: the Streaming Linked Data framework 39 M.Balduini, E.Della Valle, D.Dell'Aglio, M.Tsytsarau, T.Palpanas, and C.Confalonieri: Social Listening of City Scale Events Using the Streaming Linked Data Framework. International Semantic Web Conference (2) 2013: 1-16 Stream Bus AnalyserDecorator Adapter Publisher VisualizerStream HTTP HTTP Data Source Streaming Linked Data Server HTML5 Browser
  39. 39. http://emanueledellavalle.org - Emanuele Della Valle Processing Social Streams  Decoration at work 40 Happily into a bottle of Heineken bear #heinekendesignweek @ the Heineken Magazzini City-Scale Event: Milano Design Week Event: Heineken Design Week Location: The Magazzini hosts takesPlaceIn  M.Balduini, A.Bozzon, E.Della Valle, Y.Huang, G-J Houben: Recommending Venues Using Continuous Predictive Social Media Analytics. IEEE Internet Computing 18(5): 28-35 (2014)
  40. 40. http://emanueledellavalle.org - Emanuele Della Valle Processing Social Streams  predictive models were built • For hastags and semantic entities systematically present • Using a Holt-Winter method • grouping the frames by – working and week-end days and – Early morning, morning, afternoon, evening, and late night • Analysing 300,000 geo-located micro-posts collected other 6 months in Milano area (november 2013, aprile 2014) • It takes few seconds per hashtag/semantic entity on a 60€/month VM in a IaaS 41 Data Fitted Forecast Lower 2,5% Upper 97,5%
  41. 41. http://emanueledellavalle.org - Emanuele Della Valle Processing Social Streams  Usage of #milan in the weeks around Milan Design Week  Subtracting the predicted usage of #milan 42 200 – 700 700 – 1100 1100 – 1400 1400 – 1900 1900 – 200 200 – 700 700 – 1100 1100 – 1400 1400 – 1900 1900 – 200 WD WE WD WE WD WE WD WE WD Milan Design Week WD WE WD WE WD WE WD WE WD
  42. 42. http://emanueledellavalle.org - Emanuele Della Valle Processing Social Streams  The difference between the observed and the predicted usage of #milan perfectly fits the usage of #mdw (the official hashtag of Milan Design Week) 43 200 – 700 700 – 1100 1100 – 1400 1400 – 1900 1900 – 200 200 – 700 700 – 1100 1100 – 1400 1400 – 1900 1900 – 200 WD WE WD WE WD WE WD WE WD Milan Design Week Anomalous usage of #milan Usage of #mdw
  43. 43. http://emanueledellavalle.org - Emanuele Della Valle Processing Social Streams  Geo-references micro-posts captured, semantically annotated, cleansed using the predictive models and analyzed in Milan area  For each pixel with at least 1 micro-post we computed  The volume related to Milano Design Week  The top-10 hashtags  The top-3 locations/events  Real-time processing was possible with our in-memory C-SPARQL engine and the Streaming Linked Data framework on a 20€/month VM in a IaaS 44 What 2013 2014 Geo-located micropost 57,154 21,782 Linked to Milano Design Week 3,569 3,499 Linked to a specific location/event 761 547
  44. 44. http://emanueledellavalle.org - Emanuele Della Valle Do socially active pixels relate to events?  socially active pixels =pixels in which we captured social media that talk about Milan Design Week  To computes • precision • recall of the socially active pixels in find pixels in pixels in the three ground truths about Milan, Brera district and Tortona district 45
  45. 45. http://emanueledellavalle.org - Emanuele Della Valle 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 46 Do socially active pixels relate to events? MilanBreraTorotna Tuesday Wednesday Thursday Friday Saturday Sunday precision
  46. 46. http://emanueledellavalle.org - Emanuele Della Valle 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 47 Do socially active pixels relate to events? MilanBreraTorotna Tuesday Wednesday Thursday Friday Saturday Sunday recall
  47. 47. http://emanueledellavalle.org - Emanuele Della Valle 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 48 Do socially active pixels relate to events? MilanBreraTorotna Tuesday Wednesday Thursday Friday Saturday Sunday precision recall
  48. 48. http://emanueledellavalle.org - Emanuele Della Valle 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.2 0.4 0.6 0.8 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 49 Do socially active pixels relate to events? MilanBreraTorotna Tuesday Wednesday Thursday Friday Saturday Sunday precision recall
  49. 49. http://emanueledellavalle.org - Emanuele Della Valle Anomalous Socially active Intersection Similar?     Are CDR-anomalous and socially active pixels similar?  Which of the following four scenarios? 50
  50. 50. http://emanueledellavalle.org - Emanuele Della Valle Are CDR-anomalous and socially active pixels similar?  More formally • Jaccard • E.g., 51 J(A,B) = 8/11 J(A,B) = 3/11 A B A B J(A,B) = |A ∩ B| |A∪B|
  51. 51. http://emanueledellavalle.org - Emanuele Della Valle 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0904:00 0907:00 0910:00 0913:00 0916:00 0919:00 0922:00 1001:00 1004:00 1007:00 1010:00 1013:00 1016:00 1019:00 1022:00 1101:00 1104:00 1107:00 1110:00 1113:00 1116:00 1119:00 1122:00 1201:00 1204:00 1207:00 1210:00 1213:00 1216:00 1219:00 1222:00 1301:00 1304:00 1307:00 1310:00 1313:00 1316:00 1319:00 1322:00 1401:00 1404:00 1407:00 1410:00 1413:00 1416:00 1419:00 1422:00 1501:00 52 Are CDR-anomalous and socially active pixels similar? BreraTorotna Tuesday Wednesday Thursday Friday Saturday Sunday recall CDR-anomalous recall socially active Jaccard
  52. 52. http://emanueledellavalle.org - Emanuele Della Valle 53 Visualizing for a casual audience
  53. 53. http://emanueledellavalle.org - Emanuele Della Valle 54 See it in action! http://youtu.be/MOBie09NHxM
  54. 54. http://emanueledellavalle.org - Emanuele Della Valle Evaluation methodology for the casual audience  Guessability study • Can you guess what I mean without any explanation?  E.g. 55 Dinosaur extinction "The Shining" by Stephen King
  55. 55. http://emanueledellavalle.org - Emanuele Della Valle Evaluation of interface guessability 56
  56. 56. http://emanueledellavalle.org - Emanuele Della Valle The patters you should have got  The CDR-anomaly and the social activity is 57 Correlated Partially correlated Not correlated
  57. 57. http://emanueledellavalle.org - Emanuele Della Valle Evaluation of interface guessability 58 Q: In Brera District the volume of social media signal is partially correlated with the value of mobile anomaly signal A: 0 0.2 0.4 0.6 0.8 1
  58. 58. http://emanueledellavalle.org - Emanuele Della Valle Evaluation of interface guessability 59 Q: In Porta Romana the volume of social media signal is strongly correlated with the value of mobile anomaly signal A: 0 0.2 0.4 0.6 0.8 1
  59. 59. http://emanueledellavalle.org - Emanuele Della Valle Evaluation of interface guessability 60 Q: In Tortona District the volume of social media signal is strongly correlated with the value of mobile anomaly signal A: 0 0.2 0.4 0.6 0.8 1
  60. 60. http://emanueledellavalle.org - Emanuele Della Valle Back to the research question 61 [photo: https://www.flickr.com/photos/debord/4932655275] Can we collect, analyse and repurpose • social media captured at place and events and • privacy-preserving aggregates of Call Data Records to allow visually • perceiving emerging patterns and • observing their dynamics? Yes! at least, in Milano Design Week 2013 and 2014 [photo: https://flic.kr/p/beuDaX ]
  61. 61. http://emanueledellavalle.org - Emanuele Della Valle 62 Take home message … guess it :-)
  62. 62. http://emanueledellavalle.org - Emanuele Della Valle 63 Take home message … guess it :-) Emanuele Della Valle emanuele.dellavalle@polimi.it http://emanueledellavalle.org
  63. 63. Listening to the pulse of our cities fusing Social Media Streams and Call Data Records Emanuele Della Valle emanuele.dellavalle@polimi.it http://emanueledellavalle.org 18th International Conference on Business Information Systems 24-26 June 2015, Poznań, Poland

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