Cyberbullying has been a difficult problem for policy makers and observers to define. For some, cyberbullying is understood as a public health problem, while others view it largely as an education issue, and still others see it as a justice problem. In Canada, while the definition of cyberbullying continues to evolve, a nascent approach assumes that it is similar to traditional face‐to‐face bullying with computer‐mediated communication as a new element. This definition is at odds with recent research on cyberbullying, which may have significant implications for policy makers seeking to design effective interventions.
Technologists, interested in demonstrating the value of data analytics products to the field of public policy, argue that analysis of social media sites can provide insights about policy perspectives among the wider public. At its core are assumptions that diverse groups can provide wise answers to social queries, and that governments can utilize crowd-sourcing as a deliberative tool to improve policy decision-making. The use of data analytics for social networking sites like Twitter could inform policymaking if it could identify areas of potential agreement among a diverse group of individuals. This paper uses the De Groot learning model to test the capacity of online crowds to come to consensus about social problems. Using this model, and the Idle No More social movement as a case, this paper examines the degree that Twitter is a "wise" crowd in terms of its structure, meaning it is capable of sustaining an inclusive exchange of information over time. The paper finds that structurally, the Twitter network is the sort that can converge on a topic, however the larger the discussion, the more the network structure will be centralized, meaning small groups can dominate the messaging. However, influential actors change over time, suggesting that network structure may not matter as much as information flows across influential events.
This paper introduces the Archives Unleashed Cloud, a web-based interface for working with web archives at scale. Current access paradigms, largely driven by the scope and scale of web archives, generally involve using the command line and writing code. This access gap means that subject-matter experts, as opposed to developers and programmers, have few options to directly work with web archives beyond the page-by-page paradigm of the Wayback Machine. Drawing on first-hand research and analysis of how scholars use web archives, we present the interface design and underpinning architecture of the Archives Unleashed Cloud. We also discuss the sustainability implications of providing a cloud-based service for researchers to analyze their collections at scale.
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