Online Communities:

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• Online Communities
• Usability, sociability, trust privacy
• Jenny Preece
• Professor of Information Systems
• UMBC, Baltimore, MD 21250, USA
• preece_at_umbc.edu
• www.ifsm.umbc.edu/onlinecommunitieswww.id-book.co
  m

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Big picture

• Online communities can play a remarkable role in
  peoples lives- information transfer- empathic
  supportTwo questions guide this work
• What is a successful online community?
• How can designers and community managers make
  online communities more successful?

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Overview

• Definitions examples
• Sociability usability
• Empathy, trust and privacy
• Final comments

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Definitions of online community

• Technologists
• Sociologists and anthropologists
• Business entrepreneurs (e-commerce)
• A virtual space where people come together to get
  or give information or support, to learn, to
  discuss, to be with others online.
• Online communities support communication between
  patients, professionals, students, citizens and
  nations
• Small or large, local, national, or
  international, virtual or physi-virtual.

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Some numbers (10/2001)

• 52m US Internet users, 55 check health sites
• 230m unique MSN users per month
• 29m AOL users, 1 million more per month
• Over 104m ICQ users, millions now texting
• Over 91,500 UseNet groups
• 50,000 IBM employees, World Jam, June 01
• 100 -150 immersive CAVE environments

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My definition (Preece, 2000)

• Purposes people come together for a purpose.
• People make the community. Group dynamics, needs
  and roles shape the community.
• Policies behavior is governed by group norms,
  rules and formal policies.
• Software supports and influences community
  activity.

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has
has
Community
make
Purposes
People
Policies
has
constitute
costitute
constitute
share
develop
norms, rules
goals, aspirations
individuals
perform
influence
influence
follow
foster
actions
constitute
constitute
operations
communications
refer_to
refer_to
require
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If you build it will they come?

• Online communities are like a park they can
  be - designed and everything put in place -
  left to evolve with no intervention - encouraged
  guided evolution
• Different strategies for different communities
• Guided evolution usually the best

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Overview

• Definitions examples
• Sociability usability
• Empathy, trust and privacy
• Final comments

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Sociability and Usability

• Sociability is concerned with human to human
  social interaction. Communities with good
  sociability have unambiguous, supportive, social
  structures.
• Usability is concerned with human-computer
  interaction. Systems with good usability are
  consistent, controllable and predictable.

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Sociability

• Purpose provide a clear statement of purpose,
  e.g., name, logo, description
• People support different types of participants
  and participation, e.g., show presence when
  appropriate, keep participants interested
• Policies guide behavior and encourage social
  norms to develope.g., moderate, support
  development of trust and reciprocity

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Usability

• Dialog social interaction support support for
  communication with recognizable icons, reduce
  typing, visualizations
• Information design distinguish between new
  old content, different types of content
• Navigation support moving around the community,
  searching messages, moving between modules
• Access consider speed of connection, not
  everyone has most recent technology

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Pillars of participatory community-centered
development

• Usability
• Dialog social interaction support
• Information design
• Navigation
• Access

• Sociability
• Purpose
• People
• Policies

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Overview

• Definitions examples
• Sociability usability
• Empathy, trust and privacy
• Final comments

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1. Empathy some excerpts

• Were all in this together, which helps!
• Thanks for this list it is nice to know youre
  not alone.
• Dr. S and Dr. B said they were amazed at how
  well I was recovering and give credit to my good
  attitude and emotional preparation for surgery ?
  I thank you all for much of that, thank you for
  your positive support.

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Definition

• Knowing what another person is feeling, feeling
  what another person is feeling and responding
  compassionately to another person
• (Levenson Reuf, 1992)

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Analysis of 500 messages (Preece, 1999)
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2. Trust

• Trust is an expectancy held by an individual or
  a group that the word, promise, verbal or written
  statement of another individual or group can be
  relied upon (Rotter, 1967)
• Predictability is implied

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Trust research in HCI

• Trust in e-commerce/web sites
• Will e-commerce sites deliver products?
• Is information on the site reliable?
• Trust in personal conversation
• Do communication partners online trust each
  other?
• What if there is no face-to-face contact, video
  or audio feedback?
• Trust is important for online support, teamwork,
  e-learning, e-healthcare

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Trust online doesnt develop quickly

• Text worst media for trust development (Bos et
  al., 2002)
• Delayed trust- relationship development
  (Walthur, 1992)
• Fragile trust - misunderstandings cause trust
  to falter
• Swift trust - willingness to show trust and
  frequent communication leads to trust (Wallace,
  1999)
• Meeting before going online helps (Rocco, 1998)
• Getting acquainted exercises help (Zheng et al.,
  2002)
• Relationship between empathy and trust blurred
  (Goleman, 1995 Ickes, 1997)

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Influence of empathy predictability on
interpersonal trust (Feng, Lazar, Preece, 2002)

• Hypothesis 1 Empathy has a positive effect on
  online interpersonal trust. The presence of
  empathic communication will increase the Rempels
  trust score.
• Hypothesis 2 Predictability has a positive effect
  on online interpersonal trust. The presence of
  predictable communication will increase the
  Rempels trust score.

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Scenarios

• Role-playing scenarios used
• A researcher communicated with subjects through
  Instant Messaging software
• A database project scenario (work-related)
• A parking scenario (more social)
• 4 different communication partners for each
  scenario, based on research design

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Research design
Predictability
Predictable
Unpredictable
Empathic
1
2
Empathy
Non-Empathic
4
3
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Research methodology

• Each of 12 subjects communicated with 4 different
  communication partners
• Subjects came back on different days for each of
  the two scenarios
• Approx. 30 minutes for each communication partner
  x 4 partners x 2 scenarios

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Measurement

• Before the scenarios took place, subjects filled
  out the Rotter Scale
• Measures general trust in society and towards
  others
• Tested and validated
• After each communication partner, subjects filled
  out the Rempel and Holmes scale
• Measures trust in a specific communication
  partner
• Tested and validated

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Results

• When conversational partners were empathic and
  predictable ? significantly higher levels of
  trust towards their partners.
• Interaction effect between empathy and
  predictability ? highest effect on the Rempel and
  Holmes trust score
• Significant correlation between liking a
  communication partner and trusting the partner

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Results

• For the database scenario, there was no
  correlation between Rempel and Holmes (partner
  trust) scores and Rotter scores (general trust)
• For the parking scenario, there was a negative
  correlation between Rempel and Holmes (partner
  trust) scores and Rotter scores (general trust)
• Suggests that in some cases, those who trust
  others FTF may not easily trust those online, and
  vice versa

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Future directions

• Different scenarios
• Medical support scenario
• More teamwork scenarios
• How do we support predictability?
• Rating/recommendation systems
• How do we support empathy online?
• Storytelling
• Templates

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3. More attention to privacy needed

• Privacy often assumed (hyper-emotional states,
  Walthur, 1996), incorrectly
• Meaningful participation often requires trust
• Trust develops slowly
• Privacy encourages trust (e.g., in support
  groups)
• Many designs pay little attention to privacy
• Privacy policies should be included, often not
• Private spaces included sometimes
• Group norms can support good behavior

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Overview

• Definitions examples
• Sociability usability
• Empathy, trust and privacy
• Final comments

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We shape our buildings, and afterwards our
buildings shape us Winston Churchill
My experience of the world is that things left
to themselves dont get right T. H. Huxley
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Im looking for project partnerswith expertise
in patient support ?
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www.ifsm.umbc.edu/onlinecommunities
www.id-book.com
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Recent publications

• Feng, J., Lazar, J., Preece, J. (2002 submitted)
  Empathic and Predictable Communication Influences
  Online Interpersonal Trust.
• Preece, J. (Ed.) (2002) Supporting Community and
  Building Social Capital. Special edition of
  Communications of the ACM, 45, 4. 37- 73.
• Preece, J. and Ghozati, K. (2001) Observations
  and Explorations of Empathy Online. In. R. R.
  Rice and J. E. Katz, The Internet and Health
  Communication Experience and Expectations. Sage
  Publications Inc. Thousand Oaks. 237-260.
• Andrews, D., Preece, J., and Turoff, M. (2002) A
  conceptual framework for demographic groups
  resistant to online community. International
  Journal of Electronic Commerce, 6, 3, 9-24.
• Preece, J. (2001) Sociability and usability
  Twenty years of chatting online. Behavior and
  Information Technology Journal, 20, 5, 347-356.
• Nonnecke, B. Preece, J. (2000) Counting the
  silent. ACM CHI2000, Hague, 73-80.
• Brown, J. R., van Dam, A., Earnshaw, R.,
  Encarnacao, J., Geudj, R., Preece, J.,
  Shneiderman, B., Vince, J. (1999) Human-centered
  computing, online communities, and virtual
  environments. IEEE Computer Graphics and
  Applications. 19, 6, 70-74.
• Lazar, J., Tsoa, R., Preece, J. (1999). One
  foot in cyberspace and the other on the ground A
  case study of analysis and design issues in a
  hybrid virtual and physical community. WebNet
  Journal Internet Technologies, Applications and
  Issues, 1(3), 49-57.
• Preece, J. (1998). Empathic communities Reaching
  out across the Web. ACM Interactions 5 (2),
  32-43.
• Preece, J. (1999). Empathic communities
  Balancing emotional and factual communication.
  Interacting with Computers, 12, 63-77.

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Other references mentioned in the talk

• Bos, N., Olson, J., Gergle, D., Olson, G. and
  Wright, Z. Effects of four computer-mediated
  communications channels on trust development, in
  Proceedings of Conference on Human Factors in
  Computing Systems (CHI) 2002 (Minneapolis MN,
  April 2002), ACM Press, 135-140.
• Goleman, D. Emotional Intelligence. Bantam Press,
  New York NY, 1995.
• Ickes, W. Empathic Accuracy. The Guildford Press,
  New York NY, 1997.
• Levenson, R. W. and Ruef, A. M. Empathy A
  Physiological substrate. The Journal of Social
  Psychology. 63. 2 (1992). 234-246.
• Meyerson, D., Weick, K.E., and Kramer, R.M. Swift
  trust and temporary systems. Trust in
  Organizations. Sage, Thousand Oaks CA, 1996,
  166-195.
• Rempel, K. J., Holmes, J. G. and Zanna, M. P.
  Trust in close relationships. Journal of
  Personality and Social Psychology. 49. 1 (1985),
  95-112.
• Rocco, E. Trust Breaks Down in Electronic
  contexts but Can Be Repaired by Some Initial
  Face-to-Face Contact, in Proceedings of
  Conference on Human Factors in Computing Systems
  (CHI) 1998 (Los Angeles CA, April 1998), ACM
  Press, 496-502.
• Rotter, J. B. A new scale for the measurement of
  interpersonal trust. Journal of Personality, 35
  (1967), 651-665.
• Wallace P. The Psychology of the Internet.
  Cambridge Cambridge University Press, Cambridge,
  UK, 1999.
• Zheng, J. Veinott, E. Bos, N. Olson, J. S. Olson,
  G. M. Trust without touch jumpstarting
  long-distance trust with initial social
  activities, in Proceedings of Conference on Human
  Factors in Computing Systems (CHI) 2002
  (Minneapolis MN, April 2002), ACM Press, 131-146.

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Additional study if time
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4. People who do not post lurkers(Nonnecke,
2000 Nonnecke Preece, 2000)

• Uncomfortable in public
• Learning about the group. Fear of going online
  before gauging ambiance of group
• Fear of persistent messages
• Not necessary to post, others have said it
• Many lurkers feel part of a communityThey are
  silent participants

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Data collection

• 12 weeks
• Started with 135 original subscriptions
• Ended with 109 DLs
• Health 77, software 21
• 147,946 messages were transcribed into records
  and imported into an SQL database.
• 60,000 members
• 19,000 posters.

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Lurking over a 3 month period

• Low lurking when- lists are small- traffic is
  high- messages are short- single posters are
  few

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New study

• 1000 MSN Communities
• 4 categories of communities
• - Health and wellness
• - Government
• - Sports and recreaction
• - Organizations
• Early results suggest strong differences in
  behavior of different groups

 
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One size does not fit all!(Babble System
Erickson et al., Chi99)