Friday 12pm, 1 November 2019
Agent, Gatekeeper, Drug Dealer: How Content Creators Craft Algorithmic Personas
Software Engineer -
Online content creators have to manage their relations with opaque, proprietary algorithms that platforms employ to rank, filter, and recommend content. How do content creators make sense of these algorithms and what does that teach us about the roles that algorithms play in the social world? We take the case of YouTube because of its widespread use and the spaces for collective sense-making and mutual aid that content creators (YouTubers) have built within the last decade. We engaged with YouTubers in one-on-one interviews, performed content analysis on YouTube videos that discuss the algorithm, and conducted a wiki survey on YouTuber online groups. This triangulation of methodologies afforded us a rich understanding of content creators’ understandings, priorities, and wishes as they relate to the algorithm. We found that YouTubers assign human characteristics to the algorithm to explain its behavior; what we have termed algorithmic personas. We identify three main algorithmic personas on YouTube: Agent, Gatekeeper, and Drug Dealer. We propose algorithmic personas as a conceptual framework that describes the new roles that algorithmic systems take on in the social world. As we face new challenges around the ethics and politics of algorithmic platforms such as YouTube, algorithmic personas describe roles that are familiar and can help develop our understanding of algorithmic power relations and potential accountability mechanisms.
In Spring 2019 Emily graduated from UC Berkeley with her M.S. in Electrical Engineering Computer Science. She emphasized in Human Computer Interaction (HCI) and her advisor was Professor Marti Hearst. In Spring 2018 Emily graduated from UC Berkeley with a BA in Computer Science and a BA in Cognitive Science. She is currently working as a software engineer in the Bay Area.