Measuring Social Media Network Effects: Evidence from Online Choice Experiments

Last registered on November 08, 2023

Pre-Trial

Trial Information

General Information

Title
Measuring Social Media Network Effects: Evidence from Online Choice Experiments
RCT ID
AEARCTR-0012300
Initial registration date
October 30, 2023

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
November 08, 2023, 11:21 AM EST

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

Locations

Region

Primary Investigator

Affiliation
Chapman University

Other Primary Investigator(s)

PI Affiliation
PI Affiliation
PI Affiliation

Additional Trial Information

Status
In development
Start date
2023-10-18
End date
2023-12-15
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract

We have already conducted a series of surveys through Lucid on individuals’ demographics, connections on a digital platform, and their valuations of these connections and digital platforms.

In this document we are pre-registering a follow-up survey and analysis plan. The survey will collect information on 2,500 users of each of four popular social media platforms (Instagram, Facebook, Twitter/X, and LinkedIn), with a focus on their number of contacts, valuation of the platform, social media usage, and other socio-economic and demographic information.

The first question we are interested in is the relationship between the number of contacts and platform valuation. Our main specification will be a linear regression with an intercept term. In secondary specifications we will replace the number of contacts with the log of the number of contacts, and include additional linear controls.

We are also interested in how platform valuations vary with socio-economic, demographic and platform usage characteristics, as well as question framing. Our main analysis will first select covariates (and their interactions) with explanatory power using LASSO. We will then run a regression of platform valuation on the LASSO selected coefficients and interactions. As secondary specifications, we will estimate how the average platform valuation varies by demographically defined sub-groups.
External Link(s)

Registration Citation

Citation
Aral, Sinan et al. 2023. "Measuring Social Media Network Effects: Evidence from Online Choice Experiments." AEA RCT Registry. November 08. https://doi.org/10.1257/rct.12300-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-10-18
Intervention End Date
2023-12-15

Primary Outcomes

Primary Outcomes (end points)
Research Questions for the Data Collection and Analysis:
>How does platform valuation vary with the number of contacts on the platform
>How does platform valuation vary with other user characteristics

Our primary outcome for both of these research questions is the monthly platform valuation of a survey taker for the platform we are asking about.
Primary Outcomes (explanation)
The platform valuation of a survey taker for the platform we are asking about. This is defined as the largest selection they answer yes to in survey question asking “In the following question, we will ask you which amounts of money (in US $) you would accept to deactivate Facebook for 1 month.”

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
See attached file describing planned data collection and analysis.
Experimental Design Details
Randomization Method
There are two levels of randomization in the study:
1) Survey takers will be randomly selected into one of three groups, each with a different top-coded value for platform valuation. This randomization will be performed through qualtrics.
2) We will then use an office computer to randomly select a subset of users to participate in a follow-up offer (See attachment for details)
3) We will finally use an office computer to randomly select an offer to make the survey taker to give up the platform for a month.
Randomization Unit
Individual survey taker
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
10,000 individual survey takers
Sample size: planned number of observations
10,000 survey takers
Sample size (or number of clusters) by treatment arms
See attached document for details
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

Documents

Document Name
Survey draft for Facebook
Document Type
survey_instrument
Document Description
Survey for Facebook users. The other surveys for Twitter, Instagram, and LinkedIn are identical (except that we ask for both number of followers and following accounts for Twitter and Instagram as opposed to just connections).
File
Survey draft for Facebook

MD5: 70337d03f608fce28ad0769817b9d6e7

SHA1: e83271ad6126b7fb1d02cd6361be025c38bba6f4

Uploaded At: October 30, 2023

Document Name
Full preregistration details
Document Type
other
Document Description
Details of our planned survey and planned main and secondary analyses.
File
Full preregistration details

MD5: ad469e25096f8311d83edf6e667b77ec

SHA1: 61e08202f9ec5487d7acb8fa7e0f97e074352761

Uploaded At: October 30, 2023

IRB

Institutional Review Boards (IRBs)

IRB Name
MIT Committee on the Use of Humans as Experimental Subjects
IRB Approval Date
2021-05-19
IRB Approval Number
E-3229

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