A project from the Social Media Research Foundation: http://www.smrfoundation.org
Smart
Society
and
Civic
Culture
About Me
Introductions
Marc A. Smith
Chief Social Scientist
Connected Action Consulting Group
Marc@connectedaction.net
htt...
Citizens are
listening and participating in
social media
• Leveraging social media for sustaining civil society
• Finding ...
4
Email (and more) is
from people to people
Patterns are left behind
http://www.flickr.com/photos/amycgx/3119640267/
Social Media Systems
World Wide Web
Each contains one or more
social networks
Early Steps
http://iparticipate.wikispaces.com
Informal Gathering
College Park, MD, April 2009
Article: Science March 2009...
www.tmsp.umd.edu
NSF Workshops: Palo Alto & DC
International Efforts
intlsocialparticipation.net
Community Informatics
Research Network
Common goods that require controlled consumption
http://flickr.com/photos/himalayan-trails/275941886/
Collective Action Dilemma Theory
• Central tenet
– Individual rationality leads to collective disaster
• Phenomena of inte...
Common goods that require collective contribution
http://flickr.com/photos/jose1jose2jose3/241450368/
World Wide Web
Each contains one or more
social networks
Telecom networks are social networks
SNA 101
• Node
– “actor” on which relationships act; 1-mode versus 2-mode networks
• Edge
– Relationship connecting nodes;...
Hardin, Garrett. 1968/1977. “The tragedy
of the commons.” Science 162: 1243-
48. Pp. 16-30 in Managing the
Commons, edited...
Location, Location, Location
Network of connections among “UMich” mentioning Twitter users
Position, Position, Position
There are many kinds of ties….
http://www.flickr.com/photos/stevendepolo/3254238329
“Think Link”
Nodes & Edges
Is related to
A B
In and Out Degree
“Think Link”
Nodes & Edges
Is related to
A B
Ties of different types
Edits
Shares membership
“Think Link”
Nodes & Edges
Is related to
Person Document
Nodes of different types
Edits
Shares membership
Collections of Connections
Centralities
• Degree
• Closeness
• Betweenness
• Eigenvector
http://en.wikipedia.org/wiki/Cent...
27
Social
Networks
• History:
from the
dawn of
time!
• Theory and
method:
1934 ->
• Jacob L.
Moreno
• http://en.wik
ipedia.or...
• Central tenet
– Social structure emerges from
– the aggregate of relationships (ties)
– among members of a population
• ...
NodeXL
Network Overview Discovery and Exploration add-in for Excel 2007/2010
A minimal network can
illustrate the ways dif...
yes no
I like you I really like youI kind of like you
I feel socially obligated to link to youI know you
I wish I knew you...
yes no
SOCIAL NETWORKS
IN TELECOM NETWORKS
Social media platforms
are a source of multiple
Social network data sets:
“Calls”
“Fri...
New Tie Granularities
• Named as friends
• Reply to message
• Poke, wave, view image
• “Gift”, “Scrap”, “Ice Cubes”
• Was ...
Two “answer people” with an emerging 3rd.
Mapping
Newsgroup
Social
Ties
Microsoft.public.windowsxp.server.general
36
Leading research: Adamic et al. 2008
Knowledge Sharing and Yahoo Answers: Everyone Knows
Something,Adamic, Lada A., Zhang ...
Communities
in Cyberspace
Analyzing Social Media Networks with NodeXL
I. Getting Started with Analyzing Social Media
Networks
1. Introduction to Soc...
NodeXL: Network Overview,
Discovery and Exploration for Excel
Leverage spreadsheet for storage of edge
and vertex data
htt...
Import from multiple
social media network
sources
Welser, Howard T., Eric Gleave, Danyel Fisher,
and Marc Smith. 2007. Visualizing the Signatures
of Social Roles in Online ...
E-mail Communication – Organization Units
• Email from the TechABC’s
organizational unit
network “backbone”,
focusing on h...
Graph Motifs
http://www.youtube.com/watch?v=0M3T65Iw3Ac
NodeXL Video
NodeXL
Free/Open Social Network Analysis add-in for Excel 2007 makes graph theory
as easy as a bar chart, integrated analy...
Bernie Hogan is a Research Fellow at the Oxford Internet
Institute at the University of Oxford. Bernie's work focuses
on t...
Facebook “ego” networks
Network Visualization
by Semantic
Substrates
Ben Shneiderman, Senior Member,
IEEE,
and Aleks Aris
IEEE TRANSACTIONS ON VIS...
Explicit vs. implicit “reputation systems”
Explicit
Statements about behaviors and
relationships
• eBay
• Amazon
• Slashdo...
59
Source: xkcd, http://xkcd.com/386/
Motivations for
contribution to
public goods
Summary: SNA tells you:
• Macro:
– What is the “shape” of the crowd?
– Are there sub-groups/clusters?
• Micro:
– Who is at...
NodeXL – next steps
• Time is of the essence!
– Contrast graph A and B
– Time series analysis of many “frames”
• Keyword n...
Join the
Social Media Research Foundation
• Contribute to the NodeXL project
– Developers, users, researchers are welcome!...
What makes it social?
• Who makes it?
• Who consumes it?
• Who owns it?/Who profits from it?
• Who or what makes it succes...
Dyadic exchanges.
Email to named
individual(s)
Committee reports to
a decision
maker/reviewer
Professional services
report...
Digital
Object
Editing
Granularity
Fine
(Character/Pixel/Byte)
Medium
(Object/Attribute/Track/Player)
Coarse
(Document/Mes...
Dimensions of Social Media:
Who can exercise what property rights
over social media?
Author
Group of
authors
Recipients Ob...
When my phone notices your phone
a new set of mobile social software applications
become possible that
capture data about ...
Interactionist
Sociology
• Central tenet
– Focus on the active effort of
accomplishing interaction
• Phenomena of interest...
Innovations in the interaction order:
45,000 years ago: Speech, body adornment
10,000 years ago: Amphitheater
5,000 years ...
Whyte, William H. 1971. City: Rediscovering the Center. New York: Anchor Books.
"All phones will be smartphones
eventually," Sanjay Jha, chief
executive of Motorola's mobile
phone business said during a...
Auto-Tweet Your Weight to the World
By ERIC A. TAUB
If you’re losing weight, why keep it to yourself? Now the whole world ...
http://www.ft.com/cms/s/0/c1473442-a6f4-11de-bd14-00144feabdc0.html
Novartis chip to help ensure bitter pills are
swallowe...
74
Trace Encounters: http://www.traceencounters.org/
Poken makes social exchanges simple and cheap:
FitBit consumer activity monitoring.
http://www.intel.com/healthcare/telehealth/
WIFE/MOTHER/WORKER/SPY
Does This Pencil Skirt Have an App?
http://www.nytimes.com/2009/09/24/fashion/24spy.html
“…a new iP...
Quantified Self:
people self-administer medical monitoring
Additional
sensors will
collect medical
data to improve
our hea...
CureTogether: http://www.curetogether.com/
Cure Together
People aggregate their self-generated medical data!
Risky behavior will be priced in
real time, 3rd glass of wine
tonight? Click here for a $20
extension for alcohol related
...
Prediction: a mobile App will be more
medically effective than many drugs
If only because it will make you take the drug
p...
A project from the Social Media Research Foundation: http://www.smrfoundation.org
Smart
Society
and
Civic
Culture
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
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  • http://www.flickr.com/photos/amycgx/3119640267/
  • Todd Beamer – United 93
  • A tutorial on analyzing social media networks is available from: casci.umd.edu/NodeXL_TeachingDifferent positions within a network can be measured using network metrics.
  • A classic of sociology—the interview question “who would you turn to for …”—is revisited.
  • Deployed in schoolsUnderstand how novice users can analyze social networksA step towards a self aware social participants –understanding how they fit, what their role is.
  • http://www.ft.com/cms/s/0/1d7e83b8-3b93-11df-a4c0-00144feabdc0.htmlSmartphone sales boom is poised to set the tone in USBy Paul Taylor in New York Published: March 30 2010 03:00 | Last updated: March 30 2010 03:00Sales of smartphones in the US such as the iPhone, BlackBerry and Motorola Droid will overtake sales of older generation "feature phones" by the end of next year, according to the Nielsen research company.Smartphone sales in the US will climb steadily over the next 18 months and account for just under 50 per cent of total sales by the autumn of next year, predicts a new report prepared by Roger Entner, an analyst in Nielsen's telecoms practice."We are just at the beginning of a new wireless era where smartphones will become the standard device consumers will use to connect to friends, the internet and the world at large," he said.Feature phones, which typically include integrated cameras and multimedia capabilities, still account for over 70 per cent of sales, but sophisticated smartphones, which can be customised with downloaded software or 'apps', are closing the gap quickly."The share of smartphones as a proportion of overall device sales has increased to 29 per cent for phone purchasers in the last six months, and 45 per cent of respondents to a Nielsen survey indicated their next device will be a smartphone," he said. His comments echo those of other industry analysts at Gartner and IDC and by phonemakers such as Sanjay Jha, chief executive of Motorola's mobile phone business."All phones will be smartphones eventually," MrJha said during a recent interview with the Financial Times.Heavy media advertising, coupled with the success of online app stores, especially Apple's which now offers over 100,000 free and low-cost apps, has helped fuel the surge in US smartphone sales over the past 18 months.Nevertheless, MrEntner forecasts further growth. At the end of last year only 21 per cent of American wireless subscribers were using a smartphone compared with 19 per cent in the previous quarter and just 14 per cent at the end of 2008."If we combine these intentional data points with falling prices and increasing capabilities of these devices along with a explosion of applications, for devices, we are seeing the beginning of a groundswell."This increase will be so rapid that by the end of 2011 Nielsen expects more smartphones in the US market than feature phones," he said.Analysts expect growth in the US to be matched in other markets.www.ft.com/businessblogCopyright The Financial Times Limited 2010. You may share using our article tools. Please don't cut articles from FT.com and redistribute by email or post to the web.
  • Applications are already getting “persuasive” – encouraging positive behaviors by tracking improvement or compliance.
  • Not only are people recording intimate medical data about themselves on an on-going basis, they are *publishing* this data to shared communities on the web. The goal is to aggregate data and insights into self treatment to build evidence and guidance for improved treatment.
  • 2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith

    1. 1. A project from the Social Media Research Foundation: http://www.smrfoundation.org Smart Society and Civic Culture
    2. 2. About Me Introductions Marc A. Smith Chief Social Scientist Connected Action Consulting Group Marc@connectedaction.net http://www.connectedaction.net http://www.codeplex.com/nodexl http://www.twitter.com/marc_smith http://delicious.com/marc_smith/Paper http://www.flickr.com/photos/marc_smith http://www.facebook.com/marc.smith.sociologist http://www.linkedin.com/in/marcasmith http://www.slideshare.net/Marc_A_Smith http://www.smrfoundation.org
    3. 3. Citizens are listening and participating in social media • Leveraging social media for sustaining civil society • Finding government services • Citizen interactions • Measuring public opinion • Identifying influential opinions • Summarizing topics of interest • Evaluating your efforts to engage in social media
    4. 4. 4 Email (and more) is from people to people
    5. 5. Patterns are left behind
    6. 6. http://www.flickr.com/photos/amycgx/3119640267/
    7. 7. Social Media Systems
    8. 8. World Wide Web Each contains one or more social networks
    9. 9. Early Steps http://iparticipate.wikispaces.com Informal Gathering College Park, MD, April 2009 Article: Science March 2009 BEN SHNEIDERMAN
    10. 10. www.tmsp.umd.edu NSF Workshops: Palo Alto & DC
    11. 11. International Efforts intlsocialparticipation.net Community Informatics Research Network
    12. 12. Common goods that require controlled consumption http://flickr.com/photos/himalayan-trails/275941886/
    13. 13. Collective Action Dilemma Theory • Central tenet – Individual rationality leads to collective disaster • Phenomena of interest – Provision and/or sustainable consumption of collective resources – Public Goods, Common Property, "Free Rider” Problems, Tragedies – Signaling intent • Methods – Surveys, interviews, participant observation, log file analysis, computer modeling (Axelrod, 1984; Hess, 1995; Kollock & Smith, 1996) Community Computer Mediated Collective Action
    14. 14. Common goods that require collective contribution http://flickr.com/photos/jose1jose2jose3/241450368/
    15. 15. World Wide Web Each contains one or more social networks
    16. 16. Telecom networks are social networks
    17. 17. SNA 101 • Node – “actor” on which relationships act; 1-mode versus 2-mode networks • Edge – Relationship connecting nodes; can be directional • Cohesive Sub-Group – Well-connected group; clique; cluster • Key Metrics – Centrality (group or individual measure) • Number of direct connections that individuals have with others in the group (usually look at incoming connections only) • Measure at the individual node or group level – Cohesion (group measure) • Ease with which a network can connect • Aggregate measure of shortest path between each node pair at network level reflects average distance – Density (group measure) • Robustness of the network • Number of connections that exist in the group out of 100% possible – Betweenness (individual measure) • # shortest paths between each node pair that a node is on • Measure at the individual node level • Node roles – Peripheral – below average centrality – Central connector – above average centrality – Broker – above average betweenness E D F A CB H G I C D E A B D E
    18. 18. Hardin, Garrett. 1968/1977. “The tragedy of the commons.” Science 162: 1243- 48. Pp. 16-30 in Managing the Commons, edited by G. Hardin and J. Baden. San Francisco: Freeman. Wellman, Barry. 1997. “An electronic group is virtually a social network.” In S. Kiesler (Ed.), The Culture of the Internet. Hillsdale, NJ: Lawrence Erlbaum. 19
    19. 19. Location, Location, Location
    20. 20. Network of connections among “UMich” mentioning Twitter users Position, Position, Position
    21. 21. There are many kinds of ties…. http://www.flickr.com/photos/stevendepolo/3254238329
    22. 22. “Think Link” Nodes & Edges Is related to A B In and Out Degree
    23. 23. “Think Link” Nodes & Edges Is related to A B Ties of different types Edits Shares membership
    24. 24. “Think Link” Nodes & Edges Is related to Person Document Nodes of different types Edits Shares membership
    25. 25. Collections of Connections Centralities • Degree • Closeness • Betweenness • Eigenvector http://en.wikipedia.org/wiki/Centrality
    26. 26. 27
    27. 27. Social Networks • History: from the dawn of time! • Theory and method: 1934 -> • Jacob L. Moreno • http://en.wik ipedia.org/wi ki/Jacob_L._ Moreno
    28. 28. • Central tenet – Social structure emerges from – the aggregate of relationships (ties) – among members of a population • Phenomena of interest – Emergence of cliques and clusters – from patterns of relationships – Centrality (core), periphery (isolates), – betweenness • Methods – Surveys, interviews, observations, log file analysis, computational analysis of matrices (Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001) Source: Richards, W. (1986). The NEGOPY network analysis program. Burnaby, BC: Department of Communication, Simon Fraser University. pp.7- 16 Social Network Theory http://en.wikipedia.org/wiki/Social_network
    29. 29. NodeXL Network Overview Discovery and Exploration add-in for Excel 2007/2010 A minimal network can illustrate the ways different locations have different values for centrality and degree
    30. 30. yes no I like you I really like youI kind of like you I feel socially obligated to link to youI know you I wish I knew you I like your picture You are cool I was paid to link to you I want your reflected glory Everybody else links to you I’d vote for you We met at a conference and it seemed like the thing to do. Can I date you? I beat you on Xbox Live Hi, Mom I have fake alter egos
    31. 31. yes no
    32. 32. SOCIAL NETWORKS IN TELECOM NETWORKS Social media platforms are a source of multiple Social network data sets: “Calls” “Friends” “Replies” “Follows” “Comments” “Reads” “Co-edits” “Co-mentions” “Co-locates” “Hybrids”
    33. 33. New Tie Granularities • Named as friends • Reply to message • Poke, wave, view image • “Gift”, “Scrap”, “Ice Cubes” • Was in the same place • Laptop is nearby • Edited same web page
    34. 34. Two “answer people” with an emerging 3rd. Mapping Newsgroup Social Ties Microsoft.public.windowsxp.server.general 36
    35. 35. Leading research: Adamic et al. 2008 Knowledge Sharing and Yahoo Answers: Everyone Knows Something,Adamic, Lada A., Zhang Jun, Bakshy Eytan, and Ackerman Mark S. , WWW2008, (2008)
    36. 36. Communities in Cyberspace
    37. 37. Analyzing Social Media Networks with NodeXL I. Getting Started with Analyzing Social Media Networks 1. Introduction to Social Media and Social Networks 2. Social media: New Technologies of Collaboration 3. Social Network Analysis II. NodeXL Tutorial: Learning by Doing 4. Layout, Visual Design & Labeling 5. Calculating & Visualizing Network Metrics 6. Preparing Data & Filtering 7. Clustering &Grouping III Social Media Network Analysis Case Studies 8. Email 9. Threaded Networks 10. Twitter 11. Facebook 12. WWW 13. Flickr 14. YouTube 15. Wiki Networks www.elsevier.com/wps/find/bookdescription.cws_home/723354/description
    38. 38. NodeXL: Network Overview, Discovery and Exploration for Excel Leverage spreadsheet for storage of edge and vertex data http://www.codeplex.com/nodexl
    39. 39. Import from multiple social media network sources
    40. 40. Welser, Howard T., Eric Gleave, Danyel Fisher, and Marc Smith. 2007. Visualizing the Signatures of Social Roles in Online Discussion Groups. The Journal of Social Structure. 8(2). Experts and “Answer People” Discussion starters, Topic setters Discussion people, Topic setters
    41. 41. E-mail Communication – Organization Units • Email from the TechABC’s organizational unit network “backbone”, focusing on high-traffic connections between units > 50 messages per FTE. • Color is mapped to Betweenness Centrality • Green vertices play important roles as bridge spanners. • Excluded nodes with low Closeness Centrality to filter out vertices that are not part of the large
    42. 42. Graph Motifs
    43. 43. http://www.youtube.com/watch?v=0M3T65Iw3Ac NodeXL Video
    44. 44. NodeXL Free/Open Social Network Analysis add-in for Excel 2007 makes graph theory as easy as a bar chart, integrated analysis of social media sources. http://nodexl.codeplex.com
    45. 45. Bernie Hogan is a Research Fellow at the Oxford Internet Institute at the University of Oxford. Bernie's work focuses on the process of networking, or maintaining connections with other people. His dissertation focused on the use of multiple media for networking while his current research on Facebook looks at the complexities of networking with multiple groups on a single site.
    46. 46. Facebook “ego” networks
    47. 47. Network Visualization by Semantic Substrates Ben Shneiderman, Senior Member, IEEE, and Aleks Aris IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. 12, NO. 5, SEPTEMBER/OCTOBER 2006 A starting list for high priority tasks on basic networks includes: T1) count number of nodes and links T2) for every node, count degree T3) for every node, find the nodes that are distance 1, 2, 3 …away T4) for every node, find betweenness centrality T5) for every node, find structural prestige T6) find diameter of the network T7) identify strongly connected or compact clusters T8) for a given pair of nodes, find shortest path between them When moving up to C2 and C3, where labels are allowed, additional tasks might be: T9) for every node/link, read the label T10) find all nodes/links with a given label/attribute
    48. 48. Explicit vs. implicit “reputation systems” Explicit Statements about behaviors and relationships • eBay • Amazon • Slashdot • Digg • MySpace • Facebook • YouTube • flickr Issues: • Provisioning: not enough rating • Latency: ratings not fast enough • Bias: susceptible to initial reactions • Collusion: easily “shilled” • Inflation: disincentives to accuracy Implicit Observations about behaviors and relationships • Google • Amazon • Flickr, MySpace, Facebook • del.icio.us • Technorati • Netscan Issues: • Ambiguity: Behavior is not endorsement • Collusion: Subject to manipulation • May be subject to “herding” or positive-feedback loops
    49. 49. 59 Source: xkcd, http://xkcd.com/386/ Motivations for contribution to public goods
    50. 50. Summary: SNA tells you: • Macro: – What is the “shape” of the crowd? – Are there sub-groups/clusters? • Micro: – Who is at the “center”? – Who is at the “edge”? – Who is the “bridge”?
    51. 51. NodeXL – next steps • Time is of the essence! – Contrast graph A and B – Time series analysis of many “frames” • Keyword networks – “semantic” associations in social media • “The Web” – Browser-based interface to NodeXL • Federated Data Collection – Array of many collectors sharing resulting data
    52. 52. Join the Social Media Research Foundation • Contribute to the NodeXL project – Developers, users, researchers are welcome! • Join the distributed data collection project – Run the data collector and share your results • Apply our tools and data to your research! http://www.smrfoundation.org
    53. 53. What makes it social? • Who makes it? • Who consumes it? • Who owns it?/Who profits from it? • Who or what makes it successful? • How to harness the swarm? • How to map and understand its dynamics? – How do people and group vary? – Who links to whom? • What is next for social media?
    54. 54. Dyadic exchanges. Email to named individual(s) Committee reports to a decision maker/reviewer Professional services reports for decision makers Local email list “Social” blogs Personal social network profile page Multiple authored specialty publications Group blogs. Personal social networks Professional reports to specialty groups Value added economic data Bloomberg Messages to discussion groups/web board Sole authored source code Popular blogs Novels Multiple authored popular media, software Journalism Wikipedia Pages Popular group blogs Collective search engine users Market behavior Query log optimizations Market analysis How large are the social groups producing and consuming social media? Individuals Small Groups Large Groups Individuals Small Groups Large Groups Producers Consumers
    55. 55. Digital Object Editing Granularity Fine (Character/Pixel/Byte) Medium (Object/Attribute/Track/Player) Coarse (Document/Message/Blog Post/Photo) Digital Object Editing Synchronicity Each user can directly control smallest units of content. Each user controls medium sized blocks of content that can only indirectly alter or be altered by other user’s content in a larger shared data structure. Each user controls a block of content, rarely edited or modified by others with only associative linkages. Synchronous Real time Shared canvas Virtual Worlds Multiplayer Games Real-time networked musical jamming Chat, IM, Twitter Asynchronous Shared docs, images, video, audio Source code Wikipedia Contribution to collected works (album, anthology, report section, discussion group, photosets and other collections). Email Blog posts Link sharing Photo sharing Document sharing Turn based games Dimensions of Social Media: How large are the pieces of social media? How interactive is the rate of exchange?
    56. 56. Dimensions of Social Media: Who can exercise what property rights over social media? Author Group of authors Recipients Observers Host Public Domain Types of property rights “What does it mean to own social media content?” Create? Copy/Paste? Edit/Delete? Limit access? Revoke access? Monitor access? Transfer to new host? Transfer rights to others? Commercial exploitation? Adjoining display rights? (can I put ads near your content when I show it to other people)? Aggregation and secondary analysis rights? Who owns social media content?
    57. 57. When my phone notices your phone a new set of mobile social software applications become possible that capture data about other people as they beacon their identifies to one another.
    58. 58. Interactionist Sociology • Central tenet – Focus on the active effort of accomplishing interaction • Phenomena of interest – Presentation of self – Claims to membership – Juggling multiple (conflicting) roles – Frontstage/Backstage – Strategic interaction – Managing one’s own and others’ “face” • Methods – Ethnography and participant observation – (Goffman, 1959; Hall, 1990)
    59. 59. Innovations in the interaction order: 45,000 years ago: Speech, body adornment 10,000 years ago: Amphitheater 5,000 years ago: Maps 150 years ago: Clock time -2 years from now: machines with social awareness
    60. 60. Whyte, William H. 1971. City: Rediscovering the Center. New York: Anchor Books.
    61. 61. "All phones will be smartphones eventually," Sanjay Jha, chief executive of Motorola's mobile phone business said during a recent interview with the Financial Times. Smartphone sales in the US will climb steadily over the next 18 months and account for just under 50 per cent of total sales by the autumn of next year http://www.ft.com/cms/s/0/1d7e83b8-3b93-11df-a4c0-00144feabdc0.html
    62. 62. Auto-Tweet Your Weight to the World By ERIC A. TAUB If you’re losing weight, why keep it to yourself? Now the whole world can know, automatically. With the Wi-Fi Connected Body Scale from Withings, a French company, everyone can know your body weight, lean and fat mass, and your B.M.I., or body mass index. The $159 scale, available from the company’s Web site and Amazon.com, automatically keeps track of up to eight users’ body stats. Step on the scale, and electrical impedance figures out your body fat. It then sends all the information via Wi-Fi to a no-charge Web site, a free iPhone app, Twitter, Google Health and Microsoft HealthVault, among others. The idea is that by amassing a continual flow of data, you’ll be able to monitor your progress in maintaining, or achieving, a healthy life style. The Wi-Fi Connected Body Scale keeps track of your weight in pounds, kilograms or stones (used in Great Britain., one stone equals 14 pounds). The eight users are distinguished by their weight. If you don’t want everyone to see the ups and downs of your avoirdupois, you can always create a Twitter account that only you (and your doctor) know about.
    63. 63. http://www.ft.com/cms/s/0/c1473442-a6f4-11de-bd14-00144feabdc0.html Novartis chip to help ensure bitter pills are swallowed By Andrew Jack in London Published: September 21 2009 23:06 technology that inserts a tiny microchip into each pill swallowed and sends a reminder to patients by text message if they fail to follow their doctors’ prescriptions. the system – which broadcasts from the “chip in the pill” to a receiver on the shoulder – on 20 patients using Diovan, a drug to lower blood pressure, had boosted “compliance” with prescriptions from 30 per cent to 80 per cent after six months.
    64. 64. 74
    65. 65. Trace Encounters: http://www.traceencounters.org/
    66. 66. Poken makes social exchanges simple and cheap:
    67. 67. FitBit consumer activity monitoring.
    68. 68. http://www.intel.com/healthcare/telehealth/
    69. 69. WIFE/MOTHER/WORKER/SPY Does This Pencil Skirt Have an App? http://www.nytimes.com/2009/09/24/fashion/24spy.html “…a new iPhone app called Lose It! Which sounds like a diet, if you ask me. For weeks he’d been keeping a food diary on his phone — all the calories he ate, and all the calories he burned — and it was constantly generating cool little charts and graphs to let him know whether he was meeting his goals. “I’ve lost 12 pounds,” he said. “Get it for me,” I hissed. “Now.” Lose It! has its own database listing the calories in a few thousand different foods. And if a food was not listed? I could always find it in another iPhone app, the LiveStrong calorie counter, which lists 450,000 foods. LoseIt! Weight Loss iPhone App
    70. 70. Quantified Self: people self-administer medical monitoring Additional sensors will collect medical data to improve our health and safety, as early adopters in the "Quantified Self" movement make clear.
    71. 71. CureTogether: http://www.curetogether.com/ Cure Together People aggregate their self-generated medical data!
    72. 72. Risky behavior will be priced in real time, 3rd glass of wine tonight? Click here for a $20 extension for alcohol related injury or illness. http://www.connectedaction.net/2009/02 /18/the-future-of-helath-insurance- mobile-medical-sensors-and-dynamic- pricing/
    73. 73. Prediction: a mobile App will be more medically effective than many drugs If only because it will make you take the drug properly
    74. 74. A project from the Social Media Research Foundation: http://www.smrfoundation.org Smart Society and Civic Culture

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