2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith
1. A project from the Social Media Research Foundation: http://www.smrfoundation.org
2. About Me
Marc A. Smith
Chief Social Scientist
Connected Action Consulting Group
3. Citizens are
listening and participating in
• 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
18. SNA 101
– “actor” on which relationships act; 1-mode versus 2-mode networks
– 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
– 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
A B D E
19. 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
29. • 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),
– Surveys, interviews, observations,
log file analysis, computational
analysis of matrices
(Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)
Source: Richards, W.
(1986). The NEGOPY
program. Burnaby, BC:
Fraser University. pp.7-
Social Network Theory
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
32. 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
34. SOCIAL NETWORKS
IN TELECOM NETWORKS
Social media platforms
are a source of multiple
Social network data sets:
35. 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
36. Two “answer people” with an emerging 3rd.
37. 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)
39. Analyzing Social Media Networks with NodeXL
I. Getting Started with Analyzing Social Media
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
9. Threaded Networks
15. Wiki Networks
48. 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
51. E-mail Communication – Organization Units
• Email from the TechABC’s
focusing on high-traffic
units > 50 messages per
• Color is mapped to
• Green vertices play
important roles as bridge
• Excluded nodes with low
Closeness Centrality to
filter out vertices that are
not part of the large
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.
55. 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.
57. Network Visualization
Ben Shneiderman, Senior Member,
and Aleks Aris
IEEE TRANSACTIONS ON VISUALIZATION
AND COMPUTER GRAPHICS, VOL. 12, NO. 5,
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
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
58. Explicit vs. implicit “reputation systems”
Statements about behaviors and
• Provisioning: not enough rating
• Latency: ratings not fast enough
• Bias: susceptible to initial reactions
• Collusion: easily “shilled”
• Inflation: disincentives to accuracy
Observations about behaviors and
• Flickr, MySpace, Facebook
• Ambiguity: Behavior is not
• Collusion: Subject to manipulation
• May be subject to “herding” or
60. Summary: SNA tells you:
– What is the “shape” of the crowd?
– Are there sub-groups/clusters?
– Who is at the “center”?
– Who is at the “edge”?
– Who is the “bridge”?
61. 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
62. 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!
63. 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?
64. Dyadic exchanges.
Email to named
Committee reports to
reports for decision makers
Local email list
network profile page
Professional reports to
Value added economic data
Popular group blogs
Collective search engine
Query log optimizations
How large are the social groups
producing and consuming social media?
Each user can directly
control smallest units
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
Each user controls a block
of content, rarely edited or
modified by others with
only associative linkages.
Synchronous Real time Shared
Real-time networked musical
Chat, IM, Twitter
Asynchronous Shared docs, images,
Contribution to collected works
(album, anthology, report
section, discussion group,
photosets and other
Turn based games
Dimensions of Social Media:
How large are the pieces of social media?
How interactive is the rate of exchange?
66. Dimensions of Social Media:
Who can exercise what property rights
over social media?
Recipients Observers Host
“What does it mean to own
social media content?”
Transfer to new host?
Transfer rights to others?
Adjoining display rights?
(can I put ads near your content when
I show it to other people)?
Aggregation and secondary
Who owns social media content?
67. 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.
• Central tenet
– Focus on the active effort of
• Phenomena of interest
– Presentation of self
– Claims to membership
– Juggling multiple (conflicting) roles
– Strategic interaction
– Managing one’s own and others’ “face”
– Ethnography and participant observation
– (Goffman, 1959; Hall, 1990)
69. 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
71. "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
72. 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
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
Novartis chip to help ensure bitter pills are
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.
Does This Pencil Skirt Have an App?
“…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
“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
81. Quantified Self:
people self-administer medical monitoring
data to improve
our health and
safety, as early
adopters in the
84. 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.
85. Prediction: a mobile App will be more
medically effective than many drugs
If only because it will make you take the drug
86. A project from the Social Media Research Foundation: http://www.smrfoundation.org
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.