NEW UPDATE: Completed trials may now upload and register supplementary documents (e.g. null results reports, populated pre-analysis plans, or post-trial results reports) in the Post Trial section under Reports, Papers, & Other Materials.
Algorithmic News Feeds, Personalization, and Democratic Outcomes: Evidence from an App Patient-Preferred Field Experiment in Italy
Initial registration date
August 03, 2020
September 01, 2020 11:40 AM EDT
This section is unavailable to the public. Use the button below
to request access to this information.
Other Primary Investigator(s)
Additional Trial Information
Algorithmic news feeds provide a combination of news stories with a very high degree of personalization. Personalized political information may affect democratic outcomes by how it bolsters false consensus beliefs, and that, in contexts of high levels of polarization, may create an artificial wedge between political parties. This paper investigates the implications of personalized news feeds, by implementing a pre-registered, globally replicable, lab-in-the-field experiment, in which subjects are treated with a custom-developed news app, and then evaluated with surveys in the changes to their political and democratic beliefs. The experiment is a patient-preferred trial to explicitly account for the impact of self-selection. Results from the pilot show that algorithmic news feed are quite powerful in determining media diets, but ineffective at changing preferences.
This intervention requires participants to download a news-feed app that collects real news headlines from all national newspapers in Italy. Subjects are asked to use the app for a period of 15 days. The app provides two manipulations, including a chronological and a personalized news-feed. Outcomes will be evaluated on a number of politically relevant variables, including voting intentions and political knowledge.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
The study includes behavioral and surveys outcomes. The app will collect information on users' behavior online, including reading time, clicks, and number, and length of sessions. Survey outcomes include political preferences, political knowledge, and second-order beliefs on others.
Primary Outcomes (explanation)
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
The experiment includes two treatment conditions (popular and personalized news feeds) and one control condition (no app). The experimental protocol includes two treatment arms, one with self-selection into treatment and one with randomized treatment. This design will allow the experimenter to develop estimates of the likelihood of users taking up treatment, and therefore estimate the outcome averages were the treatment be implemented outside of the experimental setting.
Experimental Design Details
Randomization done in office by a computer.
Treatment is assigned at the participant level.
Was the treatment clustered?
Sample size: planned number of clusters
The subject pool is of 700 users.
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
250 control, 550 treatment (50% per treatment arm).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable effect is of 0.2 standard deviations of the control group for each dependent variable.
INSTITUTIONAL REVIEW BOARDS (IRBs)
Panel on Human Subjects in Non-Medical Research
IRB Approval Date
IRB Approval Number