Psychology of Social Media: Implication for Design

Shelly D. Farnham, Ph.D.

Dec 03 2009

Yahoo

Agenda

My background and approach Psychology of social media Brief overview of past research trajectory Deeper discussion of two recent projects –>

technology and building real world community CoCollage Pathable

My Background: Industry R&D Specialize in social media

Social networks, community, identity, mobile

Early stage innovation Extremely rapid R&D cycle Study, brainstorm, design, prototype,

deploy, evaluate (repeat) Convergent evaluation methodologies:

interviews, questionnaires, usage analysis

Career PhD in Social Psych from UW 7 years Microsoft Research 4 years startup world

Personal Map

Research and Development Process

meeting social goals

Party Report 41%

Invitation 18%

Question 16%

Bond Building 15%

Request 1%

Party report w ith address

9%

Importance of Information in selecting chat partner

0

1

2

3

4

5

6

7

Rank

Rating

Similarity

Interacts with friends

Ratings by friends

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 even better?

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

Social Psychological Approach Understanding users

Individuals Social dynamics: pairs, groups,

networks

Social engineering Technologies as social

environments Technologies as interventions

Socially intelligent Use understanding of social

processes to inform design

Example

Design goal: a profile and matchmaking system to increase likelihood of two people finding each other and having a successful dating experience

Understanding Attraction Predictors of attraction

similarity frequency of exposure People I like like you

(Balance theory)

Predictors of matching Similarity of “level”

(matching hypothesis)

Process Reciprocal self-disclosure

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

Design Principles Defining user’s goals

Social goals To like myself That others like me Sense of belonging

Mastery, self-efficacy Implicit vs. explicit

What are People Using Top Facebook Applications For?

community

dating

misc fortunes

naming

social good

play game

play with digital pet

events

media sharing

tell me about me

send gift

profile enhancement

social selection

play social game

social comparison

enhanced communication

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

Design Principles

The best social technologies are “invisible” to the user need usability, to achieve

sociability Social translucence

Visibility, awareness, accountability

Influential Early Research (1999) 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 In terms of importance to self Dynamic and idiosyncratic

0 1 2 3

Face to faceEmailsPhone

Mailing listsSMS

Chat/IMBlogs

Web communityOnline games

Hours per day

35

35.5

36

36.5

37

37.5

38

38.5

39

39.5

40

Rel

atio

nsh

ip S

atis

fact

ion

Email in Relationship

Dating Committed

No

Yes

N = 46 N = 82 N = 110 N = 94

Early Studies of Social Technologies

Importance of Information in selecting chat partner

0

1

2

3

4

5

6

7

Rank

Rating

Similarity

Interacts with friends

Ratings by friends

social support

community

dating

Profiles and matchmaking

Social Networking, Community, Identity, Mobile (2000-2005)

User studies

MSR Connections

Personal Map

Point to Point

Wallop

Visualizing and interacting with personal and corporate social networks

Similarity based on interaction behavior, co-occurrence in communication groups

Enables dynamic network Extract meaningful

collections/groups via cluster analysis

Personal MapAutomatically organize contacts in a way that is meaningful/intuitive to user

Shelly Farnham::Will Portnoy

Similarity (A B) = (sum (AB * significance))/sqrt(A * B)Grouped using hierarchical cluster analysis

Infers implicit social groups from communication behavior in email

Provide sense of who’s important

Dynamic, changes as levels of interaction change

Minimal maintenance required

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49

Size of Distribution List

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

Point to Point User Studiesfacilitate knowledge exchange by exploiting corporate social network information

Point to Point User Study I

Rank of Similarity to User (1 = Most Similar)

383430262218141062

Prop

orti

on o

n L

ist

.8

.7

.6

.5

.4

.3

.2

.1

0.0

People most similar to the user tended to also be on the user’s

list of coworkers.

Rank of Similarity to User (1 = Most Similar)

383430262218141062

Prop

orti

on C

ross

ed O

ff M

ap

.8

.7

.6

.5

.4

.3

.2

.1

0.0

People most similar to the user were not crossed off map

as not belonging.

39 employees completed task Participants listed 15 closest co-workers, used to assess

accuracy of point to point map

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

Relative Status

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4

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12

Overlapping People

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0.5

1

1.5

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2.5

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Unchosen

Chosen

Organizational Distance

10.8

11.1

11.4

11.7

12.0

12.3

12.6

12.9

network information affected decision-making

Mobile Social and Hyper-coordination:Supporting Life Cycle of Events

Joe

Amy

Bob

Jen

Apart Together Apart (Repeat)

Joe Amy

Bob Jen

Joe

Bob

Amy

Jen

Shelly to coffee: caffeine?

Swarm:GroupText messaging

Slam:Groups, messaging, photo sharing for the smartphone

Groove Field Deployment Study After Katrina hurricane,

economy at a stand still, largely evacuated

Microsoft effort, Groove deployment to relief workers Secure, peer to peer

collaboration Enables sharing and

synchronization across locations, while mobile, with intermittent Internet access

Ideal for ad hoc, cross organizational collaboration

Waggle Labs (2006-2009) Social Media R&D Consulting and Incubation

CoCollage (Strands)

Swaggle (group text messaging)

Zillow community

Teen Focus Group (MSR)

Social Web 2.0

Pathable

Trusera

Reality AllStarz

Facebook analysis

City of SeattleMyTwee

Distribution of Daily Activity in Top Applications, Measured in Share of Total Daily Active Usage (28.4 million total, averaged for week ending 11/18/07)

What are People Using Top Facebook Applications For?

community

dating

misc fortunes

naming

social good

play game

play with digital pet

events

media sharing

tell me about me

send gift

profile enhancement

social selection

play social game

social comparison

enhanced communication

User Goals for Facebook Apps

CoCollage

The Strands Community Collage (CoCollage™) promotes awareness, interactions and communityin third places where people seek conversation and connection.

Web site for sharing and conversationLarge display showing “Community Collage”

Third Places Semi-public places away

from home (first places) and work (second places)

People gather to enjoy conversation with friends and strangers

Facilitate community development frequent serendipitous

interactions increased likelihood of

developing web of interpersonal relationships

Existing “Technologies” for Community Development in Third Places

Challenging to get to know who comes regularly over time, what they are like, and start conversations

CoCollage: Expanding Impact of Place

asynchronous awareness, sharing and conversation

in café or at home

synchronousawareness and conversation

in cafe

web site

large display

People and profiles

Shared items (photos & quotes)

Commenting, voting

Uploading

Messaging

The big screen

CoCollage Features

Early Deployment Study Procedure

Deploy to local coffee shop: Trabant, working closely with owners

Observations, interviews and questionnaire

Goals develop a better understanding of

the psycho-social factors that would impact adoption and use

get immediate feedback for iteratively improving design

explore how best to measure place-based community development for future studies

Factors Expected to Influence Adoption and Use The size and activity of the existing

community the extent to which the individual

has a desire to meet others through the café

the individual’s existing levels of psychological sense of community and place attachment to the café

Place Attachment Rosenbaum et al. in study of a suburban diner People who experienced social support through

diner, developed place attachment – bond between person and place

Used items that loaded highly on three factors: Functional dependency: “I get more satisfaction out of Trabant than

other cafes” Commitment: “I really care about the fate of Trabant” Identification with self: “The success of Trabant is my success”

Sense of Community

Place Attachment

Questionnaire: Existing Community Size of their existing café network:

58% had at least one acquaintance in café, of those averaging 4.2 each 25% had at least one personal friend, of those averaging 2.8 each

Psycho social factors: Satisfied with café (M = 5.6)* Lukewarm in sense of community (M = 3.5)* Place attachment on dependency (M = 5.4)* and commitment (M = 5.3)*

factors, but less so on identity (M = 3.4)*

Desire to connect with others 56% had some or more interest in meeting others at the café suggests roughly half of regulars would want to join CoCollage

*on scale of 1 to 7, where 1 = not at all and 7 = extremely so

Raw Correlations

Bolded items are statistically significant at p < .05.

Of 69 who completed questionnaire, 24 also joined CoCollage

Sense of community, place attachment, and desire to connect correlated with whether joined CoCollage

CoCollage Usage 82 users in first month

Primary usage: create a profile browse other profiles upload images View others’ images

Significant correlation between desire to make friends and number of comments

(r = .43, p < .05) number of unique days they

have returned to the system

(r = .43, p < .05)Percentage of users who engaged in each type of activity, with means

A Month Later: Impact on Place Attachment

Time 1 Time 25.3

5.4

5.5

5.6

5.7

5.8

5.9

6

6.1

6.2P

lace

Atta

chm

ent -

- D

epen

denc

y

CoCollage Users' had More Place Attachment at Time 2

A Month Later: Impact on Neighboring

Time 1 Time 20

0.5

1

1.5

2

2.5

3

3.5

Sesn

e of

Com

mun

ity --

Nei

ghbo

ring

CoCollage Users' had More a Sense of "Neighboring" at Time 2

CoCollage Study Conclusions Within first month, decent adoption

82 out of roughly 400 regulars joined CoCollage in the first month Questionnaire results shows that people who

a) are looking to connect with others

b) already have a psychological sense of community at the café

c) already feel place attachment to the café,

are more likely to join CoCollage and start conversations CoCollage did have impact on attachment and

neighboring over time

Psychological sense of community for place and place attachment are meaningful constructs in predicting adoption of a place-based community technology

Pathable: Leveraging Social Media for Professional Social Networking Whom do I most want to meet, in the limited

time available to me? How do I meet them?

EIBTM’s WorldWide Technology Watch Award for 2009

Social Networking at Events World wide over 1.2 million professional events

each year, adding up to a hundred billion dollar industry

Why? Learning Meeting people!

Forming connections with clients and colleagues Face-to-face for developing trust face-to-face for informal idea and knowledge sharing via

conversation

Building Community at Events In early interviews with conference organizers,

they listed building community as a primary goal

Why do event attendees and event hosts at professional events care about building community?

What is Community

"I define "community" as networks of interpersonal ties that provide sociability, support, information, a sense of belonging, and social identity.”

– Barry Wellman (2001)

Cupcake Society

Why Do Event Attendees Care about Community?

Sure!

Hey, I’m a member of

the Cupcake Society

too!

Can I borrow some sugar?

Sure!

Take my

recipe, too!

Community groups enable transitive relationships Powerfully increase social capital through simple act of joining

community Communities of practice: group of people interested in content

domain, shared practices increase effectiveness of members

Why Host Cares about Community

We expect that sense of community at events increases attendee loyalty.

Designing Pathable: Leveraging Social Media for Face to Face Professional Social Networking

Whom do I most want to meet, in the limited time available to me?

How do I meet them?

How do we become a “social tie”? How do we become a community?

Who is here? Who do I want to meet?

So

cial Netw

orks

So

cial S

cien

tist

Reality

AllS

tar

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ia Startu

p

Research startu

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So

cia

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Blo

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com

mu

nity

Co

mm

un

ity

blogger

social technology

Exploration at Seattle Mind Camp 3

75 people provided tags for self, organization, related people, related events

Pathable Community and

social networking tools for conferences

Community Dashboard

Profiles Attendee directory Match-making Messaging Integration (blog,

twitter, LinkedIn) Wiki (Wetpaint) Schedule

Design Themes The event host is a connector and community

moderator Rich information with minimal effort Social tags are used as pivots of awareness,

connection, and communication Professional match matching for improved

people finding Incorporate communication back channels

Profile

Per event

Profile

User can prepopulate from past event

Host can prepopulate, e.g. for speakers

Attendee Directory Searchable

Tag-centric Most used

feature

Conversation To all, or tags Subscribe to

mailing list

Contacts

Added through bookmarking

Tweet Stream Live updates

Host Manager

Face to Face Integration Using existing technologies:

Mobile Badges Printable calendar Visualization

Personalized Badge

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

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

Primary Goal in Coming to Event

0%

10%

20%

30%

40%

50%

60%

70%

80%

Have Fun Be Inspired Learn Meet Others

Primary Goals in Coming to Event

Per

cen

t

People Came to BarCamp Primarily to Network, and then to Learn

Correlations between Event Features and Intention to Return Will Come Back

Event Feature Next Year

Years to Come

r

r

Number of people met .26 .12

Professional friends at event .31 .01

Satisfaction with sessions .63 .59

Satisfaction with conversations .80 .62

Professional suport .41 .39

Sense of community .44 .78

Event attachment

dependency .62 .73

commitment .67 .79

identificaiton .31 .49

Bolded items are statistically significant at p < .05.

Sense of community and event attachment highly correlation r = .81

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 raw 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

Impact on Professional Network

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low high

Impact of Pathable on Size of Network

Num

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ofes

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Pathable Usage

Impact on Attachment and Sense of Community

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Event Attachment (Ident) Sense of Community

Low

High

PathableUsage:

Impact of Pathable Usage

Rat

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on L

iker

tSc

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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)

Figure 9. Life cycle of Pathable activity before, during and after event

Life Cycle of a Pathable-enabled Event Gnomedex

Can create an active community with minimal effort

Two emails Seeded initial

profiles Seeded

conversations

Seeding the Community Ensure the community feels full from the start Model the desired behavior

Invite the organizers, speakers, volunteers to complete a profile first

Author the speaker/high status profiles Seed representative tags Seed type of conversation hoped for Send personal invitations

Leveraging Match-making Features Nurturing tags

Use badges Use color coded categories

Provides overview Easy point of conversation Examples

Job types: developer, designer, marketer

Interests: blogging, podcasting, and mobile

Person types: creative vs. geek

Personality: introvert, extrovert Integrate with face to face

Introductions Birds of a feather meetings

People Loved Badges

and blogged about them!

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 environmentspeople, networks, and groups as primary content

Networking and community technologies can and SHOULD meaningfully impact face-to-face interactions