nfais-social discovery in an information abundant world

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Social Discovery in an Information Abundant World Ben Shneiderman [email protected] @benbendc Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Dept. of Computer Science Member, Institute for Advanced Computer Studies Miles Conrad Award Lecture NFAIS, Feb. 28, 2011

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Page 1: NFAIS-Social Discovery in an Information Abundant World

Social Discoveryin an Information Abundant World

Ben Shneiderman [email protected] @benbendc

Founding Director (1983-2000), Human-Computer Interaction LabProfessor, Dept. of Computer Science

Member, Institute for Advanced Computer Studies

Miles Conrad Award LectureNFAIS, Feb. 28, 2011

Page 2: NFAIS-Social Discovery in an Information Abundant World

Interdisciplinary research community - Computer Science & Info Studies - Psych, Socio, Poli Sci & MITH (www.cs.umd.edu/hcil)

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Design Issues

• Input devices & strategies• Keyboards, pointing devices, voice

• Direct manipulation

• Menus, forms, commands

• Output devices & formats• Screens, windows, color, sound

• Text, tables, graphics

• Instructions, messages, help

• Collaboration & Social Media

• Help, tutorials, training

• Search www.awl.com/DTUI

Fifth Edition: 2010

• Visualization

Page 4: NFAIS-Social Discovery in an Information Abundant World

Spotfire: Retinol’s role in embryos & vision

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http://registration.spotfire.com/eval/default_edu.asp

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Fact-Finding SearchNFAIS 2008

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Discovery Process: Task Analysis

Specific fact finding (known-item search) On what day was Barack Obama born? <Google succeeds>

NFAIS 2008

Page 8: NFAIS-Social Discovery in an Information Abundant World

Discovery Process: Task Analysis

Specific fact finding (known-item search) On what day was Barack Obama born? <Google succeeds>

Extended fact finding (vague query) What cities did John McCain live in since he became a Senator?

Exploration of availability (vague result request) What genealogical information on Barack Obama is at the National Archives?

NFAIS 2008

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Discovery Process: Task Analysis

Specific fact finding (known-item search) On what day was Barack Obama born? <Google succeeds>

Extended fact finding (vague query) What cities did John McCain live in since he became a Senator?

Exploration of availability (vague result request) What genealogical information on Barack Obama is at the National Archives?

Open-ended browsing and problem analysis (hidden assumptions) How has John McCain’s position on the environment changed since 2001?

Mismatch with metadata (requires exhaustive search) How has Barack Obama’s choice of clothing changed during his campaign?

NFAIS 2008

Page 10: NFAIS-Social Discovery in an Information Abundant World

Discovery Process: Task Analysis

Specific fact finding (known-item search

Extended fact finding (vague query

Exploration of availability (vague result request

Open-ended browsing and problem analysis (hidden assumptions

Mismatch with metadata (requires exhaustive search

NFAIS 2008

Page 11: NFAIS-Social Discovery in an Information Abundant World

Discovery Process: Task Analysis

Specific fact finding (known-item search

Extended fact finding (vague query

Exploration of availability (vague result request

Open-ended browsing and problem analysis (hidden assumptions

Mismatch with metadata (requires exhaustive search

1-minute

Weeks &Months

NFAIS 2008

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Discovery Process: Design Challenges

Enrich query formulation

Expand result management

Enable long-term effort

Enhance collaboration

Deal with special cases: - Legal, patent & medical searches require thoroughness - Proving non-existence is difficult - Outlier items can be critical - Bridging items can be critical

NFAIS 2008

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NFAIS 2011: Social Discovery

• Facebook minutes exceed Google minutes

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NFAIS 2011: Social Discovery

• Facebook minutes exceed Google minutes

• Social referral exceeds solitary search

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http://ukwebfocus.wordpress.com/2010/06/09/if-social-discovery-is-beating-traditional-search/

Search and Rescue: How to Become Findable and Shareable in Social Media http://searchenginewatch.com/3639969

Social Referral Exceeds Solitary Search

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NFAIS 2011: Social Discovery

• Facebook minutes exceed Google minutes

• Social referral exceeds solitary search

• Ambitious challenges generate powerful collaborations

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NFAIS 2011: Social Discovery

• Facebook minutes exceed Google minutes

• Social referral exceeds solitary search

• Ambitious challenges generate powerful collaborations

• Shift to App discovery & mobile search

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NFAIS 2011: Social Discovery

• Facebook minutes exceed Google minutes

• Social referral exceeds solitary search

• Ambitious challenges generate powerful collaborations

• Shift to App discovery & mobile search

• Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social Social

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Discovery Process: Visual Analytics

Thomas & Cook, Illuminating the Path (2004)

Sense-Making Loop

•Information Seeking

•Information Foraging

•Exploration Insight

•Present Results

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Social Discovery: New Media Lifestyle

Prosumption Cycle

•Producers & Consumers

•User Generated Content

•Crowdsourcing

•Collective Intelligence

http://www.socialtimes.com/2008/07/new-media-lifecycle-social-discovery/

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Social Bookmarking: del.icio.us & connotea

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Collaboration: Tagging & voting

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www.hivegroup.com

Treemap: Digg Overview

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Chomp: App Discovery

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Blekko:

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YAHOO! Answers

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Wikia Answers

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Quora

Search question topicsRead questions Read answers from named sourcesRate & contribute

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VIVOweb: Enabling Networking of Scientists

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Biodiversity: Encyclopedia of Life

eol.org

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NASA Clickworkers: Crowdsource Science

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Citizen Science Alliance

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Collaboratories: Discovery Communities

Bos et al.,

Olson, Gary M., Zimmerman, Ann, & Bos, Nathan. (2008) Scientific Collaboration on the Internet. MIT Press.

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Health, Healthcare & Wellness

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Social Marketplace: Mechanical Turk

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Social Challenge: Netflix Prize

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Social Search/Discovery: Active & Passive

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Social Challenge: Innocentive

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TopCoder: Asking for Programming Help

• Linux, Mozilla, Apache,...

• CrisisCamp, Sahana, Hackathons, ....

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Social Discovery

SocialDiscovery Create Capacity Seek Solution

Individual Tag, Comment, Rate, Review, Summarize

Ask questions, Offer challenge,Request collaboration, Seek experts

Community Establish thesauri,Prepare catalogs,Aggregate knowledge,Organize resources

Give answers, Respond to challenge, Discuss alternatives, Offer advice

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Reader Contributor Collaborator `AllUsers

From Reader to Leader:Motivating Technology-Mediated Social Participation

Preece & Shneiderman, AIS Trans. Human-Computer Interaction1 (1), 2009 aisel.aisnet.org/thci/vol1/iss1/5/

Leader

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Motivating Readers

Usability SociabilityInteresting & relevant content presented in attractive, well-organized layouts

Encouragement by friends, family, respected authorities, advertising

Frequently updated content with highlighting to encourage return visits

Repeated visibility in online, print, television, other media

Support for newcomers: tutorials, animated demos, FAQs, help, mentors, contacts

Understandable norms & policies

Clear navigation paths sense of mastery and control

Sense of belonging: recognition of familiar people & activities

Universal usability: novice/expert, small/large display, slow/fast network, multilingual, support for users with disabilities

Charismatic leaders with visionary goals

Interface design features to support reading, browsing, searching, sharing

Safety & privacy

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Motivating Contributors

Usability Sociability

Low threshold interfaces to encourage small contributions (no login)

Support for legitimate peripheral participation

High ceiling interfaces that allow large frequent contributions

Chance to build reputation over time while performing satisfying tasks

Visibility for users’ contributions & impact - aggregated over time

Recognition for the highest quality & quantity of contributions

Visibility of ratings & comments Recognition of a person’s specific expertise

Tools to undo vandalism, limit malicious users, control pornography & libel

Policies & norms for contributions

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Motivating Collaborators

Usability SociabilityWays to locate relevant & competent individuals to form collaborations

Atmosphere of empathy & trust that promotes belonging to the community & willingness to work within groups to produce something larger

Tools to collaborate: communicate within groups, schedule projects, assign tasks, share work products, request assistance

Altruism: a desire to support the community, desire to give back, willingness to reciprocate

Visible recognition collaborators, e.g. authorship, citations, links, acknowledgements

Ways to develop a reputation for themselves & their collaborators; develop & maintain status within group

Ways to resolve differences (e.g. voting), mediate disputes & deal with unhelpful collaborators

Respect for status within the community

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Motivating Leaders

Usability Sociability

Leaders are given higher visibility & their efforts are highlighted, sometimes with historical narratives, special tributes, or rewards

Leadership is valued and given an honored position & expected to meet expectations

Leaders are given special powers, e.g. to promote agendas, expend resources,

or limit malicious users

Respect is offered for helping others & dealing with problems

Mentorship efforts are visibly celebrated, e.g. with comments from mentees

Mentors are cultivated & encouraged

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NodeXL: Network Overview for Discovery & Exploration in Excel

www.codeplex.com/nodexl

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NodeXL: Network Overview for Discovery & Exploration in Excel

www.codeplex.com/nodexl

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NodeXL: Import Dialogs

www.codeplex.com/nodexl

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Tweets at #WIN09 Conference: 2 groups

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Tweets at #NFAIS11 Conference: Sunday

Size by Betweenness Centrality

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Tweets at #NFAIS11 Conference: Sunday

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Tweets at #NFAIS11 Conference: Monday

Size by Betweenness Centrality

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Tweets at #NFAIS11 Conference: Monday

Size by Betweenness Centrality

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Tweets at #NFAIS11 Conference: Monday

Size by Betweenness Centrality, Color by Cluster

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WWW2010 Twitter Community

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Tweets for #HCI: 2 groups

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Oil Spill Twitter Community

www.codeplex.com/nodexl/

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CHI2010 Twitter Community

www.codeplex.com/nodexl/

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NodeXL: HIPAA, F-R layout, Size by Followers

www.codeplex.com/nodexl

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NodeXL: HIPAA, H-K layout, extract smalls, size by Tweets

www.codeplex.com/nodexl

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NodeXL: HIPAA, H-K, Size by Betweenness Centrality

www.codeplex.com/nodexl

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NodeXL: HIPAA, H-K, Size by Betweenness Centrality

www.codeplex.com/nodexl

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NodeXL: HIPAA, H-K, Size by Betweenness Centrality

www.codeplex.com/nodexl

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NodeXL: HIPAA, H-K, Size by Betweenness Centrality

www.codeplex.com/nodexl

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Flickr clusters for “mouse”

Computer Mickey

Animal

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Flickr networks

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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

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Social Media Research Foundation

Researchers who want to - create open tools - generate & host open data - support open scholarship

Map, measure & understand social media  

Support tool projects to collection, analyze & visualize social media data.  

smrfoundation.org

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UN Millennium Development Goals

• Eradicate extreme poverty and hunger• Achieve universal primary education• Promote gender equality and empower women• Reduce child mortality• Improve maternal health• Combat HIV/AIDS, malaria and other diseases• Ensure environmental sustainability• Develop a global partnership for development

To be achieved by 2015

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28th Annual SymposiumMay 25-26, 2011

www.cs.umd.edu/hcil

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Social Search/Discovery: Active&Passive

• Create content: scanned & born digital• Individual & group efforts

• Improve info quality • consistency, clarity, completeness

• currency, sourced, linked

• Organize data: taxonomies, tagging, rating

• Common queries, results ranking, query refinement

• Interpreting & organizing results

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“Noovo is a social discovery platform that helps users contribute, find and share highly relevant content in the simplest possible way,”

Social media has fundamentally changed the way that people discover products, services and content. It's no longer simply about the old method of product, price and placement, it's about relevance, value and virality. As the effectiveness of traditional online marketing continues to decline, how can you be sure that your message is not only absorbed, but embraced, passed along and viewed as valuable? There have already been plenty of studies conducted that show us that word of mouth is the most trusted source of information for internet users. It's probably fair to say that word of mouth is the most trusted method of discovery and influence in general. I'm much more likely to go see a movie if a good friend tells me I'll like it versus seeing an ad. http://heavybagmedia.com/blog/2008/11/28/maximizing-social-discovery-opportunities-on-the-social-web

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Social Discovery

SocialDiscovery Create Capacity Seek Solution

Individual Tag, Comment, Rate, Review, Summarize

Ask questions, Offer challenge,Request collaboration, Seek experts

Community Establish thesauri,Prepare catalogs,Aggregate knowledge,Organize resources

Give answers, Discuss alternatives, Respond to challenge, Offer advice

Social Discovery in an Information Abundant World Ben Shneiderman [email protected] Twitter @benbendc University of Maryland, Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science, Member, Institute for Advanced Computer Studies Miles Conrad Award Lecture NFAIS, February 28, 2011

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Asking for Help

• Requests to your community

• Posts to discussion groups

• Questions to free answer services

• Questions to paid answer services• Mechanical Turk

• Quora

• Innocentive

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Forming Collaborations

• Find fellow searchers with shared interests

• Hire staff to follow your leadership

• Recruit domain experts to work with you

• Hire team to provide diverse skills

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Social Search/Discovery: Active & Passive

• Early systems: GroupSearch, CoSearch, Ariadne

• Tagging: Digg, Connotea

• Rating, Ranking, Reviewing

• Social Search: Wikia Search

• Facebook & Twitter requests

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U.S. Library of Congress

• Scholars, Journalists, Citizens

• Teachers, Students

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Visible Human Explorer (NLM)

• Doctors

• Surgeons

• Researchers

• Students

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NASA Environmental Data

• Scientists

• Farmers

• Land planners

• Students

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Bureau of the Census

• Economists, Policy makers, Journalists

• Teachers, Students

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NSF Digital Government Initiative

• Find what you need

• Understand what you Find

www.ils.unc.edu/govstat/

Census,NCHS, BLS, EIA,

NASS, SSA

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Recovery.gov

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Information Visualization

• Visual bandwidth is enormous• Human perceptual skills are remarkable

• Trend, cluster, gap, outlier...

• Color, size, shape, proximity...

• Three challenges• Meaningful visual displays of massive data

• Interaction: widgets & window coordination

• Process models for discovery:

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ManyEyes: A web sharing platform

http://manyeyes.alphaworks.ibm.com/manyeyes