# Algorithmic Distortion of Informational Landscapes

## TL;DR

This paper reviews how algorithms influence informational landscapes, affecting user autonomy and social processes, by examining biases in information arrangement and their impact on expanding or limiting user horizons.

## Contribution

It introduces a framework to analyze algorithmic biases on information structuring and emphasizes the importance of social context in understanding these effects.

## Key findings

- Algorithms can both expand and limit users' cognitive and social horizons.
- Biases in information rearrangement are influenced by underlying social processes.
- Differentiates between effects of algorithms on prior and posterior information.

## Abstract

The possible impact of algorithmic recommendation on the autonomy and free choice of Internet users is being increasingly discussed, especially in terms of the rendering of information and the structuring of interactions. This paper aims at reviewing and framing this issue along a double dichotomy. The first one addresses the discrepancy between users' intentions and actions (1) under some algorithmic influence and (2) without it. The second one distinguishes algorithmic biases on (1) prior information rearrangement and (2) posterior information arrangement. In all cases, we focus on and differentiate situations where algorithms empirically appear to expand the cognitive and social horizon of users, from those where they seem to limit that horizon. We additionally suggest that these biases may not be properly appraised without taking into account the underlying social processes which algorithms are building upon.