using social psychology to motivate contributions to online

USING SOCIAL PSYCHOLOGY TO

MOTIVATE CONTRIBUTIONS TO

ONLINE COMMUNITIESA presentation by Mário Carranca, based on the paper by:

Beenen et al,

Carnegie Mellon University

University of Michigan

University of Minnesota

University of Pittsburgh

MOTIVATION People benefit from others’ activities in

online communities Several online communities fail. The

reasons vary, but there’s a main one

Lack of contribution

FACTS GNUtella

66% of users do not seed files87% of files are seeded by 10% of users

Open source community4% of open source users account for 50% of all

user-to-user help4% of developers contribute 88% of new code

and 66% of code fixes

MovieLensMore than 20% of the movies listed have so

few ratings that the algorithms don’t work

STUDY OBJECTIVES1. Look into social phenomena in social

science and social psychology theories

2. Elaborate on people’s behaviour in online communities

3. Implement alternative designs for which theories predict different outcomes

4. Verify the application of these theories in online communities

THEORIES Collective Effort Model (Karau, Williams)

Social LoafingSalience of UniquenessSalience of benefit and the beneficiaryCombining uniqueness and benefit

MOVIELENS

A case study

WHAT IS MOVIELENS Web-based movie recommender

community People can rate, review, and receive

recommendations for movies 7000 users active in the six month

period before research

FRAMING CONTRIBUTION UNIQUENESS AND BENEFIT

Study 1

HYPOTHESES Hypothesis 1

MovieLens users will rate more movies when the uniqueness of their contribution is made salient

Hypothesis 2 MovieLens users will rate more movies when the

personal benefit they receive from doing so is more salient

MovieLens users will rate more movies when the benefit for the community is more salient

Hypothesis 3 MovieLens users will rate more movies when the

perception of both unique contribution and benefits to the community are made salient than when only unique contribution or benefits are made salient

METHOD OF STUDYING Subjects

830 active MovieLens users who had rated rarely-rated movies

E-mails Variables manipulated

Uniqueness Highlighting uniqueness Highlighting non-uniqueness

Benefit No benefit Self-benefit Benefit to others Benefit to self and others

Participation data measured over one week

RESULTS

HYPOTHESES Hypothesis 1

MovieLens users will rate more movies when the uniqueness of their contribution is made salient

CONFIRMED Hypothesis 2

MovieLens users will rate more movies when the personal benefit they receive from doing so is more salient

MovieLens users will rate more movies when the benefit for the community is more salient

Hypothesis 3 MovieLens users will rate more movies when the

perception of both unique contribution and benefits to the community are made salient than when only unique contribution or benefits are made salient

RESULTS

HYPOTHESES Hypothesis 1

MovieLens users will rate more movies when the uniqueness of their contribution is made salient

CONFIRMED Hypothesis 2

MovieLens users will rate more movies when the personal benefit they receive from doing so is more salient

MovieLens users will rate more movies when the benefit for the community is more salient

DISCONFIRMED Hypothesis 3

MovieLens users will rate more movies when the perception of both unique contribution and benefits to the community are made salient than when only unique contribution or benefits are made salient

RESULTS

HYPOTHESES Hypothesis 1

MovieLens users will rate more movies when the uniqueness of their contribution is made salient

CONFIRMED Hypothesis 2

MovieLens users will rate more movies when the personal benefit they receive from doing so is more salient

MovieLens users will rate more movies when the benefit for the community is more salient

DISCONFIRMED Hypothesis 3

MovieLens users will rate more movies when the perception of both unique contribution and benefits to the community are made salient than when only unique contribution or benefits are made salient

NOT SUPPORTED

GOAL-SETTINGStudy 2

HYPOTHESES Hypothesis 4

In an online community, specific, numeric goals will motivate greater contributions than non-specific goals

Hypothesis 5 Members assigned individual goals will

provide more contributions than members assigned group goals

Hypothesis 6 In an online community, contribution will

drop off when goals exceed some difficulty threshold

METHOD OF STUDYING Subjects:

834 recently active members E-mails Variables manipulated

Group assignment Individual Group

Specificity of goals “Do your best” Numeric goal

RESULTS

HYPOTHESES Hypothesis 4

In an online community, specific, numeric goals will motivate greater contributions than non-specific goals

CONFIRMED Hypothesis 5

Members assigned individual goals will provide more contributions than members assigned group goals

Hypothesis 6 In an online community, contribution will drop

off when goals exceed some difficulty threshold

RESULTS

HYPOTHESES Hypothesis 4

In an online community, specific, numeric goals will motivate greater contributions than non-specific goals

CONFIRMED Hypothesis 5

Members assigned individual goals will provide more contributions than members assigned group goals

DISCONFIRMED Hypothesis 6

In an online community, contribution will drop off when goals exceed some difficulty threshold

RESULTS

HYPOTHESES Hypothesis 4

In an online community, specific, numeric goals will motivate greater contributions than non-specific goals

CONFIRMED Hypothesis 5

Members assigned individual goals will provide more contributions than members assigned group goals

DISCONFIRMED Hypothesis 6

In an online community, contribution will drop off when goals exceed some difficulty threshold

WEAK SUPPORT

DISCUSSION

HYPOTHESES AND RESULTS

HYPOTHESES AND RESULTS

FOOD FOR THOUGHT Challenging goals are powerful motivators

Especially when participant is not part of a group!

Goals that are overly difficult to attain may result in reduced contributions

Possibility of developing optimization algorithms!

Parts of the Collaborative Effort Model were disconfirmed

People didn’t exert less effort despite knowing their effort was being pooled rather than made identifiable

Other theories to be explored Group cohesion and identity, interpersonal

attraction, altruism

MÁRIO CARRANCA

April 2009