Psychology of Social Media:Implication for Design

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An overview of a social psychological approach to the design of social technologies, with design principles and a brief review of how I applied these principles to several R&D projects in the past few …

An overview of a social psychological approach to the design of social technologies, with design principles and a brief review of how I applied these principles to several R&D projects in the past few years.

This presentation was given to the Seattle chapter of IxDA in October 2009.

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  • 1. Psychology of Social Media: Implication for Design
    Shelly D. Farnham, Ph.D.
    Oct 19 2009
    IxDA
  • 2. My Background: Industry R&D
    • Specialize in social media
    Social networks, community, mobile
    Early stage innovation
    Extremely rapid R&D cycle
    study, brainstorm, design, prototype, evaluate (repeat)
    Career
    PhD in Social Psych from UW
    7 years Microsoft Research
    4 years startup world
    Personal Map
  • 3. Research and Development Process
    meeting social goals
  • 4. Waggle Labs: Social Media R&D Consulting and Incubation
    Pathable
    Swaggle (group text messaging)
    Zillow community
    Trusera
    CoCollage (Strands)
    Facebook analysis
    Social Web 2.0
    Reality AllStarz
    Teen Focus Group (MSR)
    City of Seattle
    Twitterdinks
  • 5. Core Problem
    Human social behavior evolved in different context than what we have today
    We are still figuring out how to interact via tech
    How is it different?
    How do we make it better?
  • 6. Why Interact through Technology?
    At a distance, over time
    Access to greater number of people
    More frequent, continues access
    Interactions archived
    Integrate with digital content
    Identity and context manipulation
    Large scale collaboration, coordination
  • 7. Social Psychological Approach
    Understanding users
    Individuals
    Social dynamics: pairs, groups, networks
    Phenomenological nature of social experiences
    Social engineering
    Technologies as social environments
    Technologies as interventions
    Focus on supporting social goals
    Socially intelligent
    Use understanding of social processes to inform design
  • 8. Example
    Design goal: a profile and matchmaking system to increase likelihood of two people finding each other and having a successful dating experience
  • 9. Understanding Attraction
    Predictors of attraction
    similarity
    frequency of exposure
    Balance theory
    Predictors of matching
    matching hypothesis
    Process
    Reciprocal self-disclosure
  • 10. Impact on Design
    Match on similarity in demographics, lifestyle
    Provide opportunities for frequent exposure, interaction
    Match based on equivalence in desirability
    Put in social context (see friends, friends of friends)
    Varying levels of communication: pseudonymous, identified, asynchronous, realtime
  • 11. Design Principles
    Defining user’s goals
    Social goals
    To like myself
    That others like me
    Sense of belonging
    Mastery, self-efficacy
    Implicit vs. explicit
  • 12. Design Principles
    Take perspective of user
    What is there, and what think is there, not always the same
    People respond to what they *think* is there
    Behavior is function of person and situation
    To predict and change behavior, must understand all the forces
    Some internal, some physical, MANY SOCIAL
    http://synapticstimuli.com/wp-content/uploads/2009/05/force_fields.jpg
  • 13. Design Principles
    The best social technologies are invisible to the user
    Need usability, to achieve sociability
    Social translucence
    Visibility, awareness, accountability
  • 14. Influential Early Research
    • HutchWorld Study:
    #1 reason patients used Internet was to interact with family and friends, not to meet other cancer patients/caregivers
    • Mall Study:
    How do people naturally model their social relations?
    • Relationships and groups
    • 15. In terms of importance to self
    • 16. Dynamic and idiosyncratic
  • Social Networking, Community, Mobile
    User studies
    MSR Connections
    • Visualizing and interacting with personal and corporate social networks
    • 17. Similarity based on interaction behavior, co-occurrence in communication groups
    • 18. Users found graph visualizations too complicated
    • 19. How extract meaning of collections/groups?
    Personal Map
    Point to Point
    Wallop
  • 20. Personal MapAutomatically organize contacts in a way that is meaningful/intuitive to user
    • Infers implicit social groups from communication behavior in email
    • 21. Provide sense of who’s important
    • 22. Dynamic, changes as levels of interaction change
    • 23. Minimal maintenance required
    Similarity (A B) = (sum (AB * significance))/sqrt(A * B)
    Grouped using hierarchical cluster analysis
    Shelly Farnham::Will Portnoy
  • 24. Point to Point User Studiesfacilitate knowledge exchange by exploiting corporate social network information
    At Microsoft:
    75,000 mailing lists,
    each person belongs to on average 11 mailing lists
    Social network info presented relative to self
    Shelly Farnham::Will Portnoy
  • 25. Point to Point User Study I
    39 employees completed task
    Participants listed 15 closest co-workers, used to assess accuracy of point to point map
    People most similar to the user were not crossed off map as not belonging.
    People most similar to the user tended to also be on the user’s list of coworkers.
  • 26. Point to Point User Study II
    17 employees completed 16 choices using Point to Point
    Study design: Participants decided between two randomly selected people whom they would like to meet for knowledge exchange
    network information affected decision-making
  • 27. Leveraging Social Media for Professional Social Networking
    Whom do I most want to meet, in the limited time available to me?
    Similar to me
    Complementary skills/needs
    Notable
    How do I meet them?
  • 28. Who is here? Who do I want to meet?
  • 29. Social Networks
    Social Scientist
    Media Startup
    Research
    SocialTech
    Community
    RealityAllStar
    BlogHer
    Blogger
    startup
    community
    social technology
    blogger
  • 30.
  • 31.
  • 32. Social Networks Online
    LinkedIn, MySpace
    Lists of who’s connected to whom
    Visualizations
    Graphs
    Need more summarization!
  • 33. Social Tagging
    Add tags as you bookmark
    Individual motivation
    Across people, importance emerges
    collective knowledge
    Browse people and related content
    Tags as pivots
  • 34. Exploration at Seattle Mind Camp 3
    75 people provided tags for self, organization, related people, related events
  • 35. Pathable
    Community and social networking tools for conferences
  • 36. Design Themes
    The event host is a connector and community moderator
    Social tags are used as pivots of awareness, connection, and communication
    Professional match matching for improved people finding
    Incorporate communication back channels
  • 37. Face to Face Integration
    Using existing technologies:
    Mobile
    Badges
    Printable calendar
    Visualization
  • 38. Personalized Badge
  • 39. Match-making
    Best matches possible, with minimal effort in profiles
    Based on predictors of successful matches:
    Common interests
    Same roles
    Job title
    Host provided categories
    Co-location
    By geography
    By events
    Existing shared groups and communities
    Weighted sum to produce ordered list
  • 40. Why Host Cares about Community
    We expect that sense of community at events increases attendee loyalty.
  • 41. Pathable BarCamp Seattle Study
    Questions:
    how important is social networking at events
    can Pathable help?
    BarCamp Seattle is a free, two-day conference held for Web 2.0
    280 people registered for the event using Pathable
    78 people total (76% male and 24% female) completed the questionnaire, 18 at the event and 60 afterwards online
  • 42. Primary Goal in Coming to Event
  • 43. Correlations between Event Features and Intention to Return
    Sense of community and event attachment highly correlation r = .81
    Bolded items are statistically significant at p < .05.
  • 44. Pathable Usage
    Everyone registered through Pathable, about half actively used the system
    60% actively browsed directory
    47% actively browsed messages
    19% actively sent messages
    43% intended to use directory after event
    55% intended to use communication features after event
    If they said they came to event only to learn, less likely to use Pathable (t = 2.6, p < .02)
    The higher the usage, the more they said it helped them meet people (r = .65, p < .001)
    No correlation between usage and count of people met
    Usage correlated with count of professional friends at event (r = .36, p < .01)
    **percentages for those who indicated at least somewhat or quite a bit
  • 45. Impact on Professional Network
  • 46. Impact on Attachment and Sense of Community
  • 47. Impact of Usage by Feature
    Pathable helped attendees meet others
    the more they browsed the attendee directory
    (r = .37, p < .005)
    the more they browsed attendee messages
    (r = .43, p < .005)
    the more they sent messages
    (r =.54, p < .005)
    the more they used the match-making feature
    (r = .66, p < .005)
  • 48. Themes and Conclusions
    Mission
    Help people meet goals through social technologies
    Incorporate psychology of social media
    Clearly define user goals
    Examine psycho-social context of technology to influence design
    Prototyping and *early* deployment to assess technology’s ability to meet goals
    Broad conclusions
    Important to map natural social processes into social technologies
    People are *always* seeking to develop social relationships, even in professional environments
    Networking and community technologies can and SHOULD meaningfully impact face-to-face interactions