The effects of algorithmic gatekeeping on individuals’ political efficacy

Partners: University of Amsterdam
Type: PhD
Duration: 2023—2026

Algorithm is one of the main actors to undertake the information curation process nowadays. Algorithmic gatekeepers like recommender systems may determine to a large extent what information individuals see, which in turn may shape their beliefs. Among all the beliefs, political efficacy is widely recognized as an indicator of the health of representative democracy. It encompasses people’s confidence in their competency to participate in politics (internal efficacy), beliefs in system’s responsiveness (external efficacy), and beliefs in their community’s ability to reach a collective goal (collective efficacy). This research project investigates the effects of a media environment increasingly dominated by digital platforms and algorithmic feedback loops, focusing on how the over-time dynamics between users, political information, and algorithms influence political efficacy. 

This PhD project will be conducted in three phrases: 

1. We will adopt a cross-platform approach to study recommender systems’ influence on political information perception and political efficacy among a representative Dutch population. 
2. Combining digital trace data and self-reported answers, our second study focuses on examining the mechanisms behind the effects of recommender on specific dimensions of political efficacy. 
3. The objective of our third phase is to test how different design of recommender systems influence individuals’ exposure to recommender systems, and their political efficacy.