Joanne E Gray
Biographic Data
| ID | 336752 |
|---|---|
| NAME | Joanne E Gray |
| GIVEN NAMES | Joanne E |
| FAMILY NAME | Gray |
| SIGNATURE | GRAY J E |
| AFFILIATIONS | The University of Sydney |
| VERIFIED | No |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 7 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Governing Social Virtual Reality
Just a little hack’
As social media platforms adapt their rules to limit the presence, spread, and amplification of harmful content on their services, users develop strategies to circumvent content moderation policies. To better understand cultures of content moderation circumvention, including the types of rules that Facebook users seek to circumvent, we analysed a sample of YouTube videos and Reddit threads in which users discuss content moderation circumvention. …
China's evolving stance against tech monopolies
The digital environment is dominated by monopolistic companies who possess and exercise substantial economic, political and social power to varying degrees. Globally, policymakers are striving to regulate these digital platform companies to address monopoly issues. Through a content analysis of publicly available policy and government documents, company reports, trade press and news media, we investigate key moments in the evolution of anti-monop…
What’s “Up Next”? Investigating Algorithmic Recommendations on YouTube Across Issues and Over Time
YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after the one that is currently playing. This feature has been criticized for limiting users’ exposure to a range of diverse media content and information sources; meanwhile, YouTube has reported that they have implemented various technical and policy changes to address these concerns. However, there is little publicly available data to support either the …
Copyright Gossip
This study investigates copyright discourses on YouTube. Through a qualitative content analysis of 144 YouTube videos, we explore how YouTube creators understand copyright law, how they minimize risks posed by copyright infringement, and how they navigate a highly technical and dynamic copyright enforcement ecosystem. Our findings offer insights into how digitally situated cultural producers are impacted by and respond to automated content modera…
Playing with machines
This article presents the results of methodological experimentation that utilises machine learning to investigate automated copyright enforcement on YouTube. Using a dataset of 76.7 million YouTube videos, we explore how digital and computational methods can be leveraged to better understand content moderation and copyright enforcement at a large scale.We used the BERT language model to train a machine learning classifier to identify videos in ca…
Playing with machines
This article presents the results of methodological experimentation that utilises machine learning to investigate automated copyright enforcement on YouTube. Using a dataset of 76.7 million YouTube videos, we explore how digital and computational methods can be leveraged to better understand content moderation and copyright enforcement at a large scale.We used the BERT language model to train a machine learning classifier to identify videos in ca…
Just a little hack’
As social media platforms adapt their rules to limit the presence, spread, and amplification of harmful content on their services, users develop strategies to circumvent content moderation policies. To better understand cultures of content moderation circumvention, including the types of rules that Facebook users seek to circumvent, we analysed a sample of YouTube videos and Reddit threads in which users discuss content moderation circumvention. …
China's evolving stance against tech monopolies
The digital environment is dominated by monopolistic companies who possess and exercise substantial economic, political and social power to varying degrees. Globally, policymakers are striving to regulate these digital platform companies to address monopoly issues. Through a content analysis of publicly available policy and government documents, company reports, trade press and news media, we investigate key moments in the evolution of anti-monop…
Copyright Gossip
This study investigates copyright discourses on YouTube. Through a qualitative content analysis of 144 YouTube videos, we explore how YouTube creators understand copyright law, how they minimize risks posed by copyright infringement, and how they navigate a highly technical and dynamic copyright enforcement ecosystem. Our findings offer insights into how digitally situated cultural producers are impacted by and respond to automated content modera…
Playing with machines
This article presents the results of methodological experimentation that utilises machine learning to investigate automated copyright enforcement on YouTube. Using a dataset of 76.7 million YouTube videos, we explore how digital and computational methods can be leveraged to better understand content moderation and copyright enforcement at a large scale.We used the BERT language model to train a machine learning classifier to identify videos in ca…
What’s “Up Next”? Investigating Algorithmic Recommendations on YouTube Across Issues and Over Time
YouTube’s “up next” feature algorithmically selects, suggests, and displays videos to watch after the one that is currently playing. This feature has been criticized for limiting users’ exposure to a range of diverse media content and information sources; meanwhile, YouTube has reported that they have implemented various technical and policy changes to address these concerns. However, there is little publicly available data to support either the …
Copyright Gossip
This study investigates copyright discourses on YouTube. Through a qualitative content analysis of 144 YouTube videos, we explore how YouTube creators understand copyright law, how they minimize risks posed by copyright infringement, and how they navigate a highly technical and dynamic copyright enforcement ecosystem. Our findings offer insights into how digitally situated cultural producers are impacted by and respond to automated content modera…
China's evolving stance against tech monopolies
The digital environment is dominated by monopolistic companies who possess and exercise substantial economic, political and social power to varying degrees. Globally, policymakers are striving to regulate these digital platform companies to address monopoly issues. Through a content analysis of publicly available policy and government documents, company reports, trade press and news media, we investigate key moments in the evolution of anti-monop…
Just a little hack’
As social media platforms adapt their rules to limit the presence, spread, and amplification of harmful content on their services, users develop strategies to circumvent content moderation policies. To better understand cultures of content moderation circumvention, including the types of rules that Facebook users seek to circumvent, we analysed a sample of YouTube videos and Reddit threads in which users discuss content moderation circumvention. …
Governing Social Virtual Reality
Computer Science (5 works) · World Wide Web (4 works) · Enforcement (3 works) · Hate Speech and Cyberbullying Detection (3 works) · Internet privacy (3 works) · Law (3 works) · Political science (3 works) · Data science (2 works) · Digital content (2 works) · Moderation (2 works)