algorithms

In setting out the work program for the past 12 months, the group’s shared objective was to collaborate across industry, government, and civil society “to map content-sharing algorithms and processes used by industry that may facilitate consumption of content that may increase user interest in or amplify terrorist and violent extremist content and consider positive ...

In setting out the work program for the past 12 months, the shared objective of the group was to collaborate across industry, government, and civil society “to map contentsharing algorithms and processes used by industry that may facilitate consumption of content that may increase user interest in or amplify terrorist and violent extremist content and ...

Objectives Despite popular notions of “filter bubbles” and “echo chambers” contributing to radicalization, little evidence exists to support these hypotheses. However, social structure social learning theory would suggest a hereto untested interaction effect. Methodology An RCT of new Twitter users in which participants were randomly assigned to a treatment of “filter bubble” (personalization algorithm) suppression. ...

Faced with YouTube’s continuous refusal to engage, Mozilla built a browser extension, RegretsReporter, that allows people to donate data about the YouTube videos they regret watching on the platform. Through one of the biggest crowdsourced investigations into YouTube, we’ve uncovered new information that warrants urgent attention and action from lawmakers and the public. We now ...

Policymakers have recently expressed concerns over the role of recommendation algorithms and their role in forming “filter bubbles”. This is a particularly prescient concern in the context of extremist content online; these algorithms may promote extremist content at the expense of more moderate voices. In this article, we make two contributions to this debate. Firstly, ...

Algorithms and especially recommendation algorithms play an important role online, most notably on YouTube. Yet, little is known about the network communities that these algorithms form. We analyzed the channel recommendations on YouTube to map the communities that the social network is creating through its algorithms and to test the network for homophily, that is, ...

In recent years, researchers have shown a vested interest in developing advanced information technologies, machine-learning algorithms, and risk-assessment tools to detect and analyze radical content online, with increased attention on identifying violent extremists or measuring digital pathways of violent radicalization. Yet overlooked in this evolving space has been a systematic examination of what constitutes radical ...