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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 2010-November-8-NIA - Smart Society and Civic Culture - Marc Smith Presentation Transcript

  • Smart Society and Civic Culture
    Marc A. Smith
    Chief Social ScientistConnected Action Consulting Group
    A project from the Social Media Research Foundation: http://www.smrfoundation.org
  • About Me
    Marc A. Smith
    Chief Social Scientist
    Connected Action Consulting Group
  • 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
    Email (and more) is from people to people
  • Patterns are left behind
  • http://www.flickr.com/photos/amycgx/3119640267/
  • Social Media Systems
  • Each contains one or more social networks
    World Wide Web
  • Early Steps
    Informal GatheringCollege Park, MD, April 2009
    Article: Science March 2009
  • NSF Workshops: Palo Alto & DC
  • International Efforts
    Community Informatics
    Research Network
  • Common goods that require controlled consumption
  • 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
    Surveys, interviews, participant observation, log file analysis, computer modeling
    (Axelrod, 1984; Hess, 1995; Kollock & Smith, 1996)
    Community Computer Mediated Collective Action
  • Common goods that require collective contribution
  • Each contains one or more social networks
    World Wide Web
  • Telecom networks are social networks
  • 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
  • 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.
  • Location, Location, Location
  • Network of connections among “UMich” mentioning Twitter users
    Position, Position, Position
  • There are many kinds of ties….
  • “Think Link”Nodes & Edges
    Is related to
    In and Out Degree
  • “Think Link”Nodes & Edges
    Is related to
    Shares membership
    Ties of different types
  • “Think Link”Nodes & Edges
    Is related to
    Shares membership
    Nodesof different types
  • Collections of ConnectionsCentralities
  • 27
  • Social Networks
    History: from the dawn of time!
    Theory and method: 1934 ->
    Jacob L. Moreno
  • Social Network Theoryhttp://en.wikipedia.org/wiki/Social_network
    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 network analysis program. Burnaby, BC: Department of Communication, Simon Fraser University. pp.7-16
  • NodeXLNetwork Overview Discovery and Exploration add-in for Excel 2007/2010
    Heather has high betweenness
    Diane has high degree
    A minimal network can illustrate the ways different locations have different values for centrality and degree
  • 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
    Can I date you?
    Are you my friend?
    We met at a conference and it seemed like the thing to do.
    I kind of like you
    I really like you
    I like you
    I feel socially obligated to link to you
    I know you
    I beat you on Xbox Live
    Hi, Mom
    I have fake alter egos
  • Are you my friend?
  • Social NetworkSin 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”
  • 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
  • Mapping Newsgroup Social Ties
    Two “answer people” with an emerging 3rd.
  • Leading research: Adamic et al. 2008
    Knowledge Sharing and Yahoo Answers: Everyone Knows Something,Adamic, Lada A., Zhang Jun, BakshyEytan, and Ackerman Mark S. , WWW2008, (2008)
  • Communities in Cyberspace
  • 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 AnalysisII. NodeXL Tutorial: Learning by Doing 4. Layout, Visual Design & Labeling 5. Calculating & Visualizing Network Metrics  6. Preparing Data & Filtering 7. Clustering &GroupingIII Social Media Network Analysis Case Studies 8. Email 9. Threaded Networks 10. Twitter 11. Facebook   12. WWW 13. Flickr 14. YouTube  15. Wiki Networks 
  • NodeXL: Network Overview, Discovery and Exploration for Excel
    Leverage spreadsheet for storage of edge and vertex data
  • Import from multiple social media networksources
  • 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 people, Topic setters
    Discussion starters, Topic setters
  • 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 component.
  • 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 analysis of social media sources.
  • 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.
  • Facebook “ego” networks
  • 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
    Network Visualization by Semantic Substrates
    Ben Shneiderman, Senior Member, IEEE,
    and AleksAris
    IEEE TRANSACTIONS ON Visualization and Computer graphics, vol. 12, no. 5, september/october 2006
  • Explicit vs. implicit “reputation systems”
    Statements about behaviors and relationships
    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 relationships
    Flickr, MySpace, Facebook
    Ambiguity: Behavior is not endorsement
    Collusion: Subject to manipulation
    May be subject to “herding” or positive-feedback loops
  • 59
    Motivations for contribution to public goods
    Source: xkcd, http://xkcd.com/386/
  • 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”?
  • 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
  • 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!
  • 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?
  • Producers
    How large are the social groups producing and consuming social media?
    Small Groups
    Large Groups
    Small Groups
    Large Groups
  • Dimensions of Social Media:
    How large are the pieces of social media?
    How interactive is the rate of exchange?
  • Who owns social media content?
    Dimensions of Social Media:
    Who can exercise what property rights over social media?
  • 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.
  • InteractionistSociology
    Central tenet
    Focus on the active effort of accomplishing interaction
    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)
  • 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
  • Whyte, William H. 1971. City: Rediscovering the Center. New York: Anchor Books.
  • 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
    "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.
  • Auto-Tweet Your Weight to the World
    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.
  • 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.
  • 74
  • Trace Encounters: http://www.traceencounters.org/
  • Poken makes social exchanges simple and cheap:
  • FitBit consumer activity monitoring.
  • http://www.intel.com/healthcare/telehealth/
    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 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
  • 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.
  • 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 injury or illness.
  • Prediction: a mobile App will be more medically effective than many drugs
    If only because it will make you take the drug properly
  • Smart Society and Civic Culture
    Marc A. Smith
    Chief Social ScientistConnected Action Consulting Group
    A project from the Social Media Research Foundation: http://www.smrfoundation.org