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Peer Effects in Online Environments: Evidence from MovieLens
Last registered on April 19, 2018

Pre-Trial

Trial Information
General Information
Title
Peer Effects in Online Environments: Evidence from MovieLens
RCT ID
AEARCTR-0002905
Initial registration date
April 16, 2018
Last updated
April 19, 2018 11:20 AM EDT
Location(s)
Primary Investigator
Affiliation
Other Primary Investigator(s)
Additional Trial Information
Status
In development
Start date
2018-04-18
End date
2018-07-25
Secondary IDs
Abstract
I conduct a field experiment on MovieLens to examine how various factors mediate peer effects.
External Link(s)
Registration Citation
Citation
Leung, Weiwen. 2018. "Peer Effects in Online Environments: Evidence from MovieLens." AEA RCT Registry. April 19. https://doi.org/10.1257/rct.2905-1.0.
Former Citation
Leung, Weiwen. 2018. "Peer Effects in Online Environments: Evidence from MovieLens." AEA RCT Registry. April 19. http://www.socialscienceregistry.org/trials/2905/history/28526.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2018-04-18
Intervention End Date
2018-07-25
Primary Outcomes
Primary Outcomes (end points)
Contributions of ratings and tags, number of logins, number of movies added to the database
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We manipulate group size, mean of group contribution, and standard deviation of group contribution to examine how these factors mediate the treatment effect of leaderboards. We also are able to examine the effect of leaderboards themselves.
Experimental Design Details
Randomization Method
Randomization done by a Python script
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
Not applicable as randomization is done at the individual level
Sample size: planned number of observations
Around 3000
Sample size (or number of clusters) by treatment arms
The main aim is to examine how the treatment effect of a leaderboard is affected by group size, mean of group contributions, as well as standard deviation of group contributions. The treatment effect of a leaderboard will be also estimated, but through within-subject/regression discontinuity/difference-in-differences methods. As such, this section is not really applicable.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
University of Minnesota
IRB Approval Date
2018-08-17
IRB Approval Number
STUDY00000968
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS