Building on Rieder’s (2015) approach to describe the structure and dynamics of outputs of the YouTube ranking algorithm, this paper seeks to interrogate YouTube’s role in the curation of content and culture production with regards to different socio-cultural issues. By examining over time the ordered videos returned by YouTube when querying “Islam”, “Syria”, “Trump”, “refugees” and “Gamergate” we seek to explore YouTube ranking culture around different issues. First, we describe and compare the outcomes of the algorithmic work, and second we qualitatively analyse the top results over time and for each issue
Since launching as a website for everyday video-sharing in 2005, YouTube has become one of the world...
International audienceThe success of YouTube has profoundly changed the face of industries dealing w...
YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after th...
Building on Rieder’s (2015) approach to describe the structure and dynamics of outputs of the YouTub...
Algorithms, as constitutive elements of online platforms, are increasingly shaping everyday sociabil...
Algorithms, as constitutive elements of online platforms, are increasingly shaping everyday sociabil...
YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after th...
YouTube's "up next" feature algorithmically selects, suggests, and displays videos to watch after th...
Drawing on the idea of platform observability, this paper combines computational and qualitative met...
Over the past 15 years, YouTube has emerged as a large and dominant social media service, giving ris...
This article is concerned with how different agencies play out in shaping public debate online and, ...
YouTube’s ‘up next’ feature algorithmically suggests videos to watch after a video that is c...
International audienceThis article presents an exploratory study of the network of associations amon...
This article is concerned with how different agencies play out in shaping public debate online and, ...
This article presents an exploratory study of the network of associations among 22,141 YouTube music...
Since launching as a website for everyday video-sharing in 2005, YouTube has become one of the world...
International audienceThe success of YouTube has profoundly changed the face of industries dealing w...
YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after th...
Building on Rieder’s (2015) approach to describe the structure and dynamics of outputs of the YouTub...
Algorithms, as constitutive elements of online platforms, are increasingly shaping everyday sociabil...
Algorithms, as constitutive elements of online platforms, are increasingly shaping everyday sociabil...
YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after th...
YouTube's "up next" feature algorithmically selects, suggests, and displays videos to watch after th...
Drawing on the idea of platform observability, this paper combines computational and qualitative met...
Over the past 15 years, YouTube has emerged as a large and dominant social media service, giving ris...
This article is concerned with how different agencies play out in shaping public debate online and, ...
YouTube’s ‘up next’ feature algorithmically suggests videos to watch after a video that is c...
International audienceThis article presents an exploratory study of the network of associations amon...
This article is concerned with how different agencies play out in shaping public debate online and, ...
This article presents an exploratory study of the network of associations among 22,141 YouTube music...
Since launching as a website for everyday video-sharing in 2005, YouTube has become one of the world...
International audienceThe success of YouTube has profoundly changed the face of industries dealing w...
YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after th...