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Purpose: The study makes use of situational crime prevention framework for analyzing online community reactions to the banning of deepfake pornographic content from Reddit.…
Purpose: The study makes use of situational crime prevention framework for analyzing online community reactions to the banning of deepfake pornographic content from Reddit.
Methodology/approach: Qualitative text analysis of user comments posted to Reddit’s rule-change announcement (N = 582) was carried out. Analysis relied on the original 25 techniques of situational crime prevention that were adapted into a table of activities and mechanisms meant specifically for use with online platforms.
Findings: Analysis indicates that Reddit users voiced several shortcomings that are currently present in Reddit’s platform management approach. In particular, users emphasized issues related to the lack of a consistent and transparent approach to community rule enforcement, as users believed the rule changes to be sudden and poorly reasoned. The general reactionary nature of Reddit’s approach to moderating community-harming actions also was a point of emphasis, alongside the platform’s continued rigid stance on freedom of expression, even with regard to illegal and demeaning content. Regarding Reddit and the new rules on involuntary pornography and the sexualization of minors, enforcement of sitewide policy appears contingent on external influences, such as attention from mainstream media or financial matters, rather than stemming from an inherent stance on decreasing community-harming activities.
Research limitations: The study only pertains to a specific rule change by Reddit and subsequent reactions from the platform’s community. Future research is needed to test the applicability of the adapted table of 25 techniques of situational crime prevention in the context of other online platforms.
Originality/value: First, the study applies the situational crime prevention approach in the context of moderating online platforms. Second, results from the study shed light on current practices in online content moderation from the perspective of criminological theory, as well as inform specific actions that can be taken to decrease the presence of community-harming phenomena and improve the enforcement of sitewide policy rules in general. Finally, by adapting the original 25 techniques of situational crime prevention to online content moderation, the study suggests a tentative roadmap for similar research in the future.
INTERNATIONAL: Deepfakes exploit social media fault
Perpetrators of technology-facilitated gender-based violence are taking advantage of increasingly automated and sophisticated privacy-invasive tools to carry out their…
Perpetrators of technology-facilitated gender-based violence are taking advantage of increasingly automated and sophisticated privacy-invasive tools to carry out their abuse. Whether this be monitoring movements through stalkerware, using drones to nonconsensually film or harass, or manipulating and distributing intimate images online such as deepfakes and creepshots, invasions of privacy have become a significant form of gender-based violence. Accordingly, our normative and legal concepts of privacy must evolve to counter the harms arising from this misuse of new technology. Canada's Supreme Court recently addressed technology-facilitated violations of privacy in the context of voyeurism in R v Jarvis (2019) . The discussion of privacy in this decision appears to be a good first step toward a more equitable conceptualization of privacy protection. Building on existing privacy theories, this chapter examines what the reasoning in Jarvis might mean for “reasonable expectations of privacy” in other areas of law, and how this concept might be interpreted in response to gender-based technology-facilitated violence. The authors argue the courts in Canada and elsewhere must take the analysis in Jarvis further to fully realize a notion of privacy that protects the autonomy, dignity, and liberty of all.
The nonconsensual taking or sharing of nude or sexual images, also known as “image-based sexual abuse,” is a major social and legal problem in the digital age. In this…
The nonconsensual taking or sharing of nude or sexual images, also known as “image-based sexual abuse,” is a major social and legal problem in the digital age. In this chapter, we examine the problem of image-based sexual abuse in the context of digital platform governance. Specifically, we focus on two key governance issues: first, the governance of platforms, including the regulatory frameworks that apply to technology companies; and second, the governance by platforms, focusing on their policies, tools, and practices for responding to image-based sexual abuse. After analyzing the policies and practices of a range of digital platforms, we identify four overarching shortcomings: (1) inconsistent, reductionist, and ambiguous language; (2) a stark gap between the policy and practice of content regulation, including transparency deficits; (3) imperfect technology for detecting abuse; and (4) the responsibilization of users to report and prevent abuse. Drawing on a model of corporate social responsibility (CSR), we argue that until platforms better address these problems, they risk failing victim-survivors of image-based sexual abuse and are implicated in the perpetration of such abuse. We conclude by calling for reasonable and proportionate state-based regulation that can help to better align governance by platforms with CSR-initiatives.
Articles containing the bogus quotes were shared across social media globally. The case illustrates how disinformation is created and spread for malign influence, and its…
With the rise of artificial intelligence and machine learning, competitive data science platforms like Kaggle are gaining momentum. From a host's perspective, the…
With the rise of artificial intelligence and machine learning, competitive data science platforms like Kaggle are gaining momentum. From a host's perspective, the platforms offer access to a large crowd of data scientists who can solve their data science problems efficiently and cost-effectively. From the participant's perspective, the platforms provide the opportunity to apply their skills to real-world problems, interact with other data scientists, and win prizes. The chapter provides an overview of competitive data science platforms and assesses their potential for business and academia. A series of opportunities and challenges of data competitions are outlined, and a concrete case is illustrated. The chapter also demonstrates common pitfalls that hosts of data competitions need to be aware of by discussing the relevance of problem definition, data leakage, and metrics to evaluate different solutions.