Algorithmic Curation. Encyclopedia of Political Communication.

Abstract

Algorithmic curation has emerged as a significant force shaping political communication in the digital era. This process involves actively selecting and organizing information to cater to individual preferences and moderate harmful content, greatly impacting the flow of information and potentially the formation of public opinion. Algorithmic personalization and content moderation are integral components of algorithmic curation. By leveraging vast amounts of data, algorithms aim to deliver personalized experiences to users, aligning content with their interests and past behaviors and to contain content that violates platform guidelines, such as misinformation, hate speech, explicit material, or harassment. However, concerns have been raised about potential biases and unintended consequences of algorithmic decision-making. Algorithmic curation has profound implications for democratic processes, as it can reinforce existing beliefs, impede exposure to diverse perspectives and create filter bubbles. Understanding the complexities of algorithmic curation in the realm of political communication is therefore crucial for researchers, policymakers, and society at large. Balancing personalization and the promotion of diverse viewpoints is essential to foster an informed and engaged citizenry in the digital age.