Algorithmic Curation. Encyclopedia of Political Communication.

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 (algorithmic personalization) but also to moderate harmful content (content moderation), both of which potentially impact the flow of information and 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 delete content that violates platform guidelines, such as 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 hinder exposure to diverse perspectives, facilitate the emergence of filter bubbles, and potentially reinforce existing beliefs. Understanding the complexities of algorithmic curation in the realm of political communication is crucial for researchers, policymakers, and society at large. Balancing personalization and moderation with the promotion of diverse viewpoints is essential to foster an informed and engaged citizenry in the digital age.