Motivating Contributions to Public Information Goods: A Field Experiment at Wikipedia

Last registered on January 18, 2019
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Pre-Trial

Trial Information

General Information

Title
Motivating Contributions to Public Information Goods: A Field Experiment at Wikipedia
RCT ID
AEARCTR-0002920
Initial registration date
April 27, 2018

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
April 30, 2018, 6:21 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
January 18, 2019, 9:19 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
United States of America
Region

Primary Investigator

Name
Fangzhou Zhang
Affiliation
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Yan Chen
PI Affiliation
University of Michigan
Contact Investigator

Additional Trial Information

Status
Completed
Start date
2016-05-06
End date
2016-12-22
Keywords
Education, Labor
Additional Keywords
JEL code(s)
H4
Secondary IDs
Abstract
Wikipedia is among the most important information sources for the general public. Motivating domain experts to contribute to Wikipedia can improve the accuracy and completeness of its content. In a field experiment at Wikipedia, we examine individual motivations to contribute to public information goods. Using a 2-by-3 factorial design, we vary the expectation on the number of recipients along one dimension and the amount of private benefit along the other dimension. In the analysis, we will investigate how our interventions affect the experts' willingness to participate and contribution measured by both quantity and quality.
External Link(s)

Registration Citation

Citation
Chen, Yan and Fangzhou Zhang. 2019. "Motivating Contributions to Public Information Goods: A Field Experiment at Wikipedia." AEA RCT Registry. January 18. https://doi.org/10.1257/rct.2920-5.0
Former Citation
Chen, Yan and Fangzhou Zhang. 2019. "Motivating Contributions to Public Information Goods: A Field Experiment at Wikipedia." AEA RCT Registry. January 18. https://www.socialscienceregistry.org/trials/2920/history/40335
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Experimental Details

Interventions

Intervention(s)
We implement a 2-by-3 between-experts factorial design in which we vary the email content inviting experts' contribution to Wikipedia articles. Along one dimension, we vary the experts' expectation on the number of recipients of the public information goods which they contribute to. In the average view condition, we provide the experts with only the average number of views a typical Wikipedia article received in the past 30 days. This information serves to set the experts' expectation on the readership of a typical Wikipedia article. In the high view condition, we provide the experts with the additional information on the number of views the recommended articles received in the past 30 days.

Along the second dimension, we vary the experts' expectation on the amount of private benefit they receive from their contribution. We include three conditions: a baseline condition, a citation condition and an acknowledgement condition. The baseline condition serves as a control and no private benefit is mentioned in the email. In the citation condition, we mention that the articles recommended to the experts are likely to cite their research. The acknowledgement condition strengthens the private benefit by including acknowledgement as an additional benefit. The experts are told in the email message that their contributions will be addressed on a WikiProject Economics page at Wikipedia. WikiProject Economics is a collection of editors who work together as a team to improve articles related to economics. Being acknowledged for one's contribution in the WikiProject Economics thus serves as a private benefit in additional to the citation benefit. To avoid potential confound due to the experts' sequential contribution, we only post the acknowledgement to the contributions from the experts in our pilot stage and keep the acknowledgement page frozen at the through the main experiment.
Intervention Start Date
2016-05-06
Intervention End Date
2016-12-22

Primary Outcomes

Primary Outcomes (end points)
willingness to participate; number of words in the comment; median of overall quality of the comment
Primary Outcomes (explanation)
To measure the quality of the experts' contribution, we develop a rating protocol based on the guidance from the literature on examining peer review of manuscripts. The raters are expected to provide objective evaluations on the quality of the comments written by the experts. In our rating procedure, raters first read the associated Wikipedia article. For each piece of comment, raters start with a series of questions regarding various aspects of the comments prior to giving their overall ratings. Such a multi-item approach breaks down the global evaluation of the entire comment into concrete subcomponents and has been found to improve the inter-rate reliability for the overall quality rating.

We measure the quality of comments by the median of raters' responses to each of the three questions:
1. Please rate the overall quality of the comment.
2. Suppose you are to incorporate this comment. How helpful is it?
3. Suppose that you are to incorporate the expert's review of this Wikipedia article and you want to first break down the review into multiple comments. How many comments has the expert made to this Wikipedia article?

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We implement a 2-by-3 between-experts factorial design in which we vary the email content inviting experts' contribution to Wikipedia articles. Along one dimension, we vary the experts' expectation on the number of recipients of the public information goods which they contribute to. In the average view condition, we provide the experts with only the average number of views a typical Wikipedia article received in the past 30 days. This information serves to set the experts' expectation on the readership of a typical Wikipedia article. In the high view condition, we provide the experts with the additional information on the number of views the recommended articles received in the past 30 days.

Along the second dimension, we vary the experts' expectation on the amount of private benefit they receive from their contribution. We include three conditions: a baseline condition, a citation condition and an acknowledgement condition. The baseline condition serves as a control and no private benefit is mentioned in the email. In the citation condition, we mention that the articles recommended to the experts are likely to cite their research. The acknowledgement condition strengthens the private benefit by including acknowledgement as an additional benefit. The experts are told in the email message that their contributions will be addressed on a WikiProject Economics page at Wikipedia. WikiProject Economics is a collection of editors who work together as a team to improve articles related to economics. Being acknowledged for one's contribution in the WikiProject Economics thus serves as a private benefit in additional to the citation benefit. To avoid potential confound due to the experts' sequential contribution, we only post the acknowledgement to the contributions from the experts in our pilot stage and keep the acknowledgement page frozen at the through the main experiment.
Experimental Design Details
Randomization Method
randomization done in office by a computer
Randomization Unit
expert
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
4000 experts
Sample size: planned number of observations
4000 experts
Sample size (or number of clusters) by treatment arms
600 experts per experimental condition
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
See attachment
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
University of Michigan IRB
IRB Approval Date
2014-10-07
IRB Approval Number
HUM00090577
Analysis Plan

Analysis Plan Documents

Pre-Analysis Plan for "Motivating Contributions to Public Information Goods"

MD5: 517a82db04112c5981de29f6f2b8172f

SHA1: 447df05a0fd84f77fa1e7c0521b119642e54e899

Uploaded At: January 18, 2019

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
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