Using Social Psychology To Motivate Contributions To Online
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The paper "Using Social Psychology to Motivate Contributions to Online Communities" was presented by myself in the Cooperative Work class of 2009
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Using Social Psychology To Motivate Contributions To Online
- 1. A presentation by Mário Carranca, based on the paper by: Beenen et al, Carnegie Mellon University University of Michigan University of Minnesota University of Pittsburgh
- 2. People benefit from others’ activities in online communities Several online communities fail. The reasons vary, but there’s a main one Lack of contribution
- 3. GNUtella 66% of users do not seed files 87% of files are seeded by 10% of users Open source community 4% of open source users account for 50% of all user- to-user help 4% of developers contribute 88% of new code and 66% of code fixes MovieLens More than 20% of the movies listed have so few ratings that the algorithms don’t work
- 4. Look into social phenomena in social 1. science and social psychology theories Elaborate on people’s behaviour in online 2. communities Implement alternative designs for which 3. theories predict different outcomes Verify the application of these theories in 4. online communities
- 5. Collective Effort Model (Karau, Williams) Social Loafing Salience of Uniqueness Salience of benefit and the beneficiary Combining uniqueness and benefit
- 6. A case study
- 7. Web-based movie recommender community People can rate, review, and receive recommendations for movies 7000 users active in the six month period before research
- 8. Study 1
- 9. 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
- 10. 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
- 12. 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
- 14. 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
- 16. 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
- 17. Study 2
- 18. 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
- 19. Subjects: 834 recently active members E-mails Variables manipulated Group assignment Individual Group Specificity of goals “Do your best” Numeric goal
- 21. 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
- 23. 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
- 25. 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
- 29. 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
- 30. April 2009
Editor's Notes
- Social loafing is the tendency for individuals to expend less effort when working collectively than when working individually. A large number of variables were found to moderate social loafing. Evaluation potential, expectations of co-worker performance. task meaningfulness, and culture had especially strong influence. These findings are interpreted in the light of a Collective Effort Model that integrates elements of expectancy-value, social identify and self-validation theoriesCollective Effort Model: people will loaf less: Believing that their effort is IMPORTANT to the group’s performance Believing that their contributions in the group are IDENTIFIABLE LIKING the groupSalience of uniqueness: people will loaf if they feel their contributions are REDUNDANT (people who rate rarely rated movies are unique and should be made aware)
- Hypothesis 4In an online community, specific, numeric goals will motivate greater contributions than non-specific goalsCONFIRMED:Meando-your-best: 10.3 movies/weekMean specific: 13.9 movies/week
- Meando-your-best: 10.3 movies/weekMean specific: 13.9 movies/week
- Hypothesis 5 Members assigned individual goals will provide more contributions than members assigned group goalsDISCONFIRMED:Group mean: 17.2 movies/weekIndividual mean: 10.4 movies/week
- Group mean: 17.2 movies/weekIndividual mean: 10.4 movies/week
- Hypothesis 6In an online community, contribution will drop off when goals exceed some difficulty thresholdWEAK SUPPORT:No statistical significance of ratings “appearing to drop with the highest goals”.
- No statistical significance of ratings “appearing to drop with the highest goals”.
- Email messages can motivate people simply by reminding them of an opportunity to contribute (telemarketers)According to the Coll. Eff. Model, it would’ve been expected that the effects of uniqueness would’ve been amplified by reminders of usefulness, but this was disconfirmed. Survey: members rate movies primarily to improve the accuracy of recommendations, and because remembering and rating is fun, and to a lesser extent, to help others.It’s possible that by contacting people who had rated rarely-rated movies, a segment of the members has been chosen who was already aware of the benefits of contributions, hence the depression.More research is needed to understand the puzzle of why subjects rated more movies when no mention was made of the benefits their ratings create for themselves of other users.
- The most robust result from this experiment was that specific goals led to higher contribution rates.A finding inconsistent with social loafing and the C.E.Model was that subjects in the ground conditions contributed MORE than those in the individual conditions.Explanations: Group conditionMISINTERPRETED as individual goals Social loafing HARD TO REPLICATE amongst volunteers(!)Suggestion that high performance goals have upper limits.
- Why did the design choices inspired by social psychology theories sometime fail to increase contribution?Failures of implementation: approach started with good theoretical approach, but badly implemented in short, single e-mails. One possible change: assertions instead of explanationsEngineering-Science mismatches: Engineering disciplines SOLVE PROBLEMS, behavioural sciences DETERMINE CAUSES OF PHENOMENAIncomplete theories: The theories do study the exact circumstances in which certain effects, such as loafing, take place. The lack of detail forces the designer to improvise when applying these theories.
- Active members: logged on at least once in 2003.Rated rarely-rated movies raters: at least 3 rarely-rated movies, or 15% of all movies rated were rarely-ratedUniqueness: “Fairly unusual tastes, you’re valuable”Non-uniqueness: “Rated movies many other subscribers have rated”No benefit: Self-benefit: rating more movies helps you!Benefit others: rating movies helps the community!Benefit self and others:Thank you e-mails
- Average: 19.26 movies/week each (before: 5.4 movies/week)Hypothesis 1MovieLens users will rate more movies when the uniqueness of their contribution is made salientCONFIRMED:Unique group rated 18% more movies than non-uniqueUnique group rated 40% more RRMovies than non-unique
- Average: 19.26 movies/week each (before: 5.4 movies/week)Hypothesis 2MovieLens users will rate more movies when the personal benefit they receive from doing so is more salientMovieLens users will rate more movies when the benefit for the community is more salientDISCONFIRMED:Mention of benefit depressed ratings rather than increased them.Benefit groups rated average of 16.36 movies/week, whereas non-benefit groups rated 28.28 movies/week
- Mention of benefit depressed ratings rather than increased them.Benefit groups rated average of 16.36 movies/week, whereas non-benefit groups rated 28.28 movies/week
- Average: 19.26 movies/week each (before: 5.4 movies/week)Hypothesis 3MovieLens 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 salientNOT SUPPORTED:There was no interaction effect between uniqueness and benefit on either overall ratings or RRMovies ratings.
- There was no interaction effect between uniqueness and benefit on either overall ratings or RRMovies ratings.
- Avg ratings per subject: 147 moviesMembers who logged in in the past five months900 originally, but 66 bounced.The quality of recommendations MovieLens makes depends on the number of ratings that members contribute. Currently, many of the movies in MovieLens have too few ratings to make accurate recommendations about them. That’s why we’re conducting a seven day campaign to increase movie ratings on MovieLens.Group assignmentSome participants were told they belonged to a group of 10 active members called “The Explorers”.10: easy to divide one’s own work shareBigger than 8: past research suggested that group goals are less effective than individual goals above group sizes of 8Specificity of goals[Together, the ten Explorers]/[You] have a goal of doing [their]/[your] best to rate additional movies over the next seven days.8/16/32/6480/160/320/6408 ratings/week baseline because it was the average weekly contribution in the pastLocke & Latham: High Performance Cycle (higher challenge goals) Self-efficacy moderates commitment to a goalNormative information about what’s expected of the personTask Satisfaction boosts future performance