Management of Negative Reviews

Last registered on March 17, 2022
View Trial History

Pre-Trial

Trial Information

General Information

Title
Management of Negative Reviews
RCT ID
AEARCTR-0009089
Initial registration date
March 13, 2022

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
March 17, 2022, 7:59 PM EDT

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

Locations

Country
United States of America
Region

Primary Investigator

Name
Ping Gong
Affiliation
Yale University
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2022-08-01
End date
2022-09-30
Keywords
Labor
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study will some insights on how crowd-sourced information platforms handles request to delete a review. We wish to evaluate how fast these requests are handled and how much we could trust information from these platform.
External Link(s)

Registration Citation

Citation
Gong, Ping. 2022. "Management of Negative Reviews." AEA RCT Registry. March 17. https://doi.org/10.1257/rct.9089-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
Intervention Start Date
2022-08-01
Intervention End Date
2022-08-02

Primary Outcomes

Primary Outcomes (end points)
How fast these reports are handled, and how many reviews are deleted
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Collect a sample of fake reviews (or reviews violating the platform's terms of service), and randomly report these reviews.
Experimental Design Details
I will carefully read through the platform's terms of service and then using textual analysis to identify reviews that violate these terms.
Randomization Method
Randomization done in office by a computer. After getting a sample of reviews, I will randomly labelled as 0 or 1. Those reviews labelled as "1" receive treatment (i.e., these reviews will be reported to the platform's data team).
Randomization Unit
A review.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
200 reviews.
Sample size: planned number of observations
200 reviews.
Sample size (or number of clusters) by treatment arms
100 control and 100 treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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