The video of this talk is available at https://www.youtube.com/watch?v=4ZdknOPY_jQ More and more we are all broadcasting information. Geolocation data, “this x sucks” data, weather data, etc. More and more that data is being parsed and analysed in realtime, such that we have now become sensors. How does this work, what does this mean, and what risks/benefits will it bring?

1. People as
Sensors
Tom Raftery
ThingMonk,
London Dec 2013.
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2. Tom Raftery
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Lead analyst, energy and
sustainability practice,
RedMonk
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GreenMonk.net
•
twitter.com/tomraftery
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tom@redmonk.com
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+34 677 695 468
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SlideShare.net/TomRaftery
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3. Mobile data
http://www.flickr.com/photos/traftery/8551389911/
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Mobile phones with GPS, accelerometers, compass, M7, barometers, moisture, etc

4. Mobile data
http://www.zeit.de/datenschutz/malte-spitz-data-retention
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Mobile phones with GPS and data retention laws
Green party sued Deutsche Telecom for data
Put it online
Source of concern

5. Social Media
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Mobile is not the only data we’re broadcasting

6. Facebook
http://newsroom.fb.com/Key-Facts
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1.19 billion monthly active users (MAU) as of September 30, 2013
727 million daily active users (DAU) in Sept 2013
874 million mobile MAUs as of September 30 2013

7. Facebook
http://techcrunch.com/2013/05/17/facebook-growth/
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Most recent usage data is from May 2013 - so well out-of-date
4.75 billion content items shared per day (status updates + wall posts + photos + videos + comments)
4.5 billion Likes per day

8. Twitter
http://hide.dyndns.info/tweetcounter/index-en.cgi
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Between 4,000-8,500 tweets per second per day
Avg over 6,000 tweets per sec, all stored in perpetuity
Tweets drop off at midnight ET, start picking up again at 6am ET!

9. Twitter
http://hide.dyndns.info/tweetcounter/index-en.cgi
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Increasing tweets per sec over the last year (max value per day used)
Two peaks on the right-hand-side

10. Twitter
http://hide.dyndns.info/tweetcounter/index-en.cgi
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Increasing tweets per day over the last year

11. Twitter
https://blog.twitter.com/2013/new-tweets-per-second-record-and-how
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Most recent numbers from Twitter:
Twitter avg - >500m TPD
Twitter avg - 5,700 TPS
Aug 2nd had a 143k TPS record (>28x the average) - no blip to service

12. Data for sale…
http://online.wsj.com/news/articles/SB10001424052702304441404579118531954483974
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Twitter in its IPO filings disclosed it is making $47.5m from selling access to its data

13. Google+
http://googleblog.blogspot.com.es/2013/10/google-hangouts-and-photos-save-some.html
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Google+
540m MAU
300m active in stream
1.5bn photos per month

14. Sina Weibo
http://sg.finance.yahoo.com/news/sina-weibo-passes-500-million-151054944.html
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China’s Sina Weibo is growing with 74% year on year user growth (http://www.chinadaily.com.cn/bizchina/2013-02/21/content_16243933.htm)
Has 220m ‘active users’ while Twitter has 170m ‘active users’ http://blogs.wsj.com/chinarealtime/2013/03/12/how-many-people-really-usesina-weibo/

15. Waze
https://www.waze.com
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Waze had an estimated 50m users in June 2013

16. Waze
https://www.waze.com
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Waze had an estimated 50m users in June 2013

17. Use Cases
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Some positive use cases of the data

18. Crowd-Sourcing
http://csce.uark.edu/~tingxiny/courses/5013spring13/readingList/crowdsource.pdf
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Academic study on feasibility of using Twitter to crowdsourced data

19. Meteorology
http://uksnowmap.com/#/
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UK Snow Map by Ben Marsh
Tweet #uksnow, postcode and x/10 rating

20. Utilities
http://greenmonk.net/2012/11/01/sustainability-social-media-and-big-data/
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GE’s Grid IQ Insight can mine social media for mentions of outages
Gives early notifications of an outage in an area
If geotagged and/or includes images/video can confirm cause of outage and speed up time to resolution

21. Utilities
http://greenmonk.net/2012/11/01/sustainability-social-media-and-big-data/
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Utilities are aware of reason for outage, speeds up time to resolution (reduces need for
investigatory truck roll)

22. Risk Analysis
http://europeandcis.undp.org/blog/2012/11/16/social-media-and-political-risk-analysis/
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United Nations Development Program & their Recorded Future project
Using publicly sourced data looking for signs of disruption or unrest

23. Risk Analysis
http://europeandcis.undp.org/blog/2012/11/16/social-media-and-political-risk-analysis/
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The same graph turned into media sources- who is talking about Georgia in this period of time

24. Risk Analysis
http://europeandcis.undp.org/blog/2012/11/16/social-media-and-political-risk-analysis/
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Mentions turned into social network analysis- who is talking to whom, who is meeting whom
“next phase will focus on conducting a regional political risk analysis and forecasting for South Eastern Europe and Central Asia”
UNDP slides courtesy of Milica Begovich (aka @elim????)

25. Automotive
http://www.magazine.pamplin.vt.edu/fall12/vehicledefects.html
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Social Media monitoring tool developed by Pamplin College of Business
Initial version worked from automotive fora and blogs, now expanding to take in Twitter and Facebook
“Robust” way to discover and classify vehicle defects from social media posts across multiple automotive brands
Faster than reporting back up through the dealer chain

26. Finance
http://arxiv.org/PS_cache/arxiv/pdf/1010/1010.3003v1.pdf
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Academic paper from University of Manchester and Indiana University shows that Twitter can predict the Dow Jones Industrial Average with 87.6%
accuracy

27. Finance
http://www.caymanatlantic.com/investment-management/4574471088
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UK Firm Derwent Capital Markets signed an exclusive deal with the authors to create a hedge fund - became Cayman Atlantic

28. Law Enforcement
http://support.sas.com/resources/papers/proceedings12/309-2012.pdf
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SAS produced an interesting white paper on this space and bought UK firm Memex - definitely chasing this space
Citing use cases like - finding individuals - analysing their social graph to find accomplices/gang structure
Also identify precursor activity to events like riots

29. Law Enforcement
http://www.policemag.com/blog/technology/story/2012/09/social-media-analytics-in-law-enforcement.aspx
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“Social media is a huge network of informants—and one you don't have to pay for.”
Law Enforcement use cases (information distribution, fake profile creation, etc.)
Helps first responders gain situational awareness prior to having feet on the ground
Helps Emergency Operations Centres gain information in the event of natural disasters, for example
Sunday’s train crash in NY, for example

30. Law Enforcement
http://www.huffingtonpost.com/2012/09/04/web-surveillance-social-media_n_1854750.html
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Other vendors in this space outlined in this article
3i-Mind - http://www.3i-mind.com/
HMS Technologies - http://www.hmstech.com/
Visible Technologies - http://www.visibletechnologies.com/
Attensity - http://www.attensity.com/home/
CrowdControlHQ - http://www.crowdcontrolhq.com/index.php
and
As well as Law Enforcement use cases (information distribution, fake profile creation, etc.)

31. Law Enforcement
http://www.lexisnexis.com/government/investigations/
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Good infographic on Law Enforcement use of social media - based on a LexisNexis Risk Solutions survey of 1,200 law enforcement professionals
Full report is available at http://solutions.lexisnexis.com/forms/GV12LEOMPSoMeSurveyforLE9677

32. Law Enforcement
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Needs to be approached sensitively - the way some of this is reported often prompts visions of ‘pre-crime’ and Minority Report

33. Smart Cities
https://itunes.apple.com/us/app/boston-citizens-connect/id330894558
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Graffiti, Pothole, & LA school district apps

34. Healthcare
http://www.google.org/flutrends/intl/en_us/
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Google use frequency of certain search terms as a way to estimate flu activity
Also have one for Dengue Fever
Search data is increasingly mobile

35. Healthcare
http://www.nature.com/nature/journal/v457/n7232/full/nature07634.html
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Google wrote this up as an academic paper and it was published in Nature

36. Healthcare
http://www.ajtmh.org/content/86/1/39.abstract
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A group led from Harvard Medical School studied viability of using social media for predicting cholera outbreak
Found that the data from Twitter closely corresponded with government data, was available up to two weeks earlier
The paper concludes informal media could be used to study the activity of other disease outbreaks around the world
Financial support was provided by Google.org

37. Healthcare
http://propellerhealth.com
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Formerly asthmapolis - wireless asthma puff data - where/when
Can map where asthma outbreaks occur - people sensitive can avoid triggers

38. Healthcare
http://www.huffingtonpost.com/keith-runyon/louisville-chooses-asthma_b_4086297.html
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Rolled out in conjunction with city of Louisville Ky
Residents experience as much as a 13-year gap in life expectancy depending upon where they live
Findings eagerly anticipated - only rolled out in Oct

39. CRM
http://www.ft.com/intl/cms/s/0/bd5a5ce2-aa57-11e1-899d-00144feabdc0.html#axzz2OAlD9lav
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T-Mobile in US analysed its 33m customer data records, web logs, billing data and social media information to predict customer defections
It halved customer defections in 3 months

40. Brand Management
http://www.youtube.com/watch?v=VaJjPRwExO8
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Nestle were Greenpeace’d because palm oil in Kit Kat came from Sinar Mas - company involved in deforestation

41. Brand Management
http://greenmonk.net/2010/03/19/can-corporate-social-responsibility-affect-your-companys-bottom-line/
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In the social media storm which followed Nestlé made every mistake in the book
Nestlé received over 200,000 protest emails and their share price was negatively affected
So they decided to work with Greenpeace to fix their supply chain and
To initiate a social media strategy for the organisation

42. Brand Management
http://uk.reuters.com/article/2012/10/26/uk-nestle-online-water-idUKBRE89P07Q20121026
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Set up a social media command centre, staffed by their Digital Acceleration Team

43. Brand Management
http://www.reputationinstitute.com/thought-leadership/global-reptrak-100
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In 2013 Nestle entered the Reputation Institute’s Global top 10 for the first time.

44. Transportation
https://twitter.com/ehn/status/396307684661530624
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Waze data now being incorporated in Google Maps

45. Transportation
http://www.bbc.co.uk/news/technology-22357748
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2.5bn anonymised call records from 5m Orange phone users in Ivory Coast
Looked at patterns of people’s movements in Abidjan - capital city of Ivory Coast
Realised they could reduce travel times of ppl by 10%

46. Looking Ahead
http://www.flickr.com/photos/35468133931@N01/8699901706
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Google Glass

47. Looking Ahead
http://www.instabeat.me
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Instabeat gives swimmers stats in their goggles as they swim
And subsequent download

48. Looking ahead
http://www.fitbit.com/force
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Fitbit force, Nike+ Fuelband, Jawbone Up
Can see a situation where sports players are broadcasting vital stats similar to F1

49. Conclusion
Data and data sources are increasing
exponentially - go hack that data for good.
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50. Thanks!
Contact information:
Tom Raftery
Principal Analyst, Energy & Sustainability, RedMonk
Tom@redmonk.com,
GreenMonk.net,
Twitter.com/tomraftery
+34 677 695 468
No tweets were hurt in the making of this presentation
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