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Down the (White) Rabbit Hole: The Extreme Right and Online Recommender Systems

Authors: 
Publication Type: 
Refereed Original Article
Abstract: 
In addition to hosting user-generated video content, YouTube provides recommendation services, where sets of related and recommended videos are presented to users, based on factors such as covisitation count and prior viewing history. This article is specifically concerned with extreme right (ER) video content, portions of which contravene hate laws and are thus illegal in certain countries, which are recommended by YouTube to some users. We develop a categorization of this content based on various schema found in a selection of academic literature on the ER, which is then used to demonstrate the political articulations of YouTube’s recommender system, particularly the narrowing of the range of content to which users are exposed and the potential impacts of this. For this purpose, we use two data sets of English and German language ER YouTube channels, along with channels suggested by YouTube’s related video service. A process is observable whereby users accessing an ER YouTube video are likely to be recommended further ER content, leading to immersion in an ideological bubble in just a few short clicks. The evidence presented in this article supports a shift of the almost exclusive focus on users as content creators and protagonists in extremist cyberspaces to also consider online platform providers as important actors in these same spaces.
Digital Object Identifer (DOI): 
10.1177/0894439314555329
Publication Status: 
Published
Date Accepted for Publication: 
Monday, 1 September, 2014
Publication Date: 
16/10/2014
Journal: 
Social Science Computer Review
Research Group: 
Institution: 
UCD
Open access repository: 
Yes
Publication document: