Designing Social Media Recommendation Algorithms for Societal Good

Introduction

Social media platforms are central for civic discourse, yet evidence is mounting that they play a causal role in deteriorating social cohesion. User behaviour on social media platforms is governed by content recommendation algorithms that maximise engagement, leading to unintended consequences such as the promotion of outrage.

Regulatory Context

The EU's newly enacted Digital Services Act mandates social media platforms to assess their systemic risks for society. However, the current challenge lies in translating abstract risks to concrete platform design changes that reduce such risks.

Project Objectives

We will bridge this gap by combining approaches from social science and computer science to incorporate the reduction of risk to civic discourse into content recommendation algorithms of social media platforms. To this end, we will:

1. Employ a participation-based approach to develop novel algorithms that consider various aspects of civic discourse, such as:

   • Information quality and diversity
   • The civility of language

2. Develop Open Source digital twins of social media platforms to enable experimentation with new algorithms independent of platform companies.

3. Balance the reduction of risk to civic discourse and freedom of expression by soliciting people's preferences in different scenarios, such as:

   • A public health crisis
   • Elections

4. Develop balanced algorithms based on the gathered preferences.

Risk Assessment Framework

Lastly, we will develop a scenario-based risk assessment framework to assess algorithms and provide policy recommendations for interventions in content recommendation algorithms.

Originality of the Project

The originality of DeSiRe stands out in that, to date, democratic values and fundamental rights played no role in the design of content recommendation algorithms.