Daniel Angus | Queensland University of Technology (original) (raw)
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articles by Daniel Angus
International Journal of Disaster Risk Reducation, 2021
In natural hazard emergencies, visual media (images, videos) document and convey the possible ris... more In natural hazard emergencies, visual media (images, videos) document and convey the possible risk, impact, and severity of the hazard. Issues arise when the visuals being circulated, at scale and speed, are manipulated, fake, or are from an unrelated event or location. These problematic visuals can impact how communities interpret the risk of an emergency. Further, when visual media present information (i.e. a cue) in conflict with what an emergency services agency is instructing the public to do, it can lead to uncertainty and confusion in the community on how to act. This research identifies four specific types of problematic visual media that are common to natural hazard emergencies in Australia. We propose a combination of reactive and proactive strategies that can be employed by emergency services agencies to manage the extent and impact of these problematic visuals.
The remote collection of speech/conversation data through smartphones can provide unique data to ... more The remote collection of speech/conversation data through smartphones can provide unique data to SLPs. But what ethico-legal aspects does a team of clinicians or researchers need to be aware of when remotely collecting such data? This presentation will discuss real-life examples of ethico-legal hurdles experienced by our research team...
Media International Australia
In this article, we examine two interrelated hashtag campaigns that formed in response to the Vic... more In this article, we examine two interrelated hashtag campaigns that formed in response to the Victorian State Government’s handling of Australia’s most significant COVID-19 second wave of mid-to-late 2020. Through a mixed-methods approach that includes descriptive statistical analysis, qualitative content analysis, network analysis, computational sentiment analysis and social bot detection, we reveal how a small number of hyper-partisan pro- and anti-government campaigners were able to mobilise ad hoc communities on Twitter, and – in the case of the anti-government hashtag campaign – co-opt journalists and politicians through a multi-step flow process to amplify their message. Our comprehensive analysis of Twitter data from these campaigns offers insights into the evolution of political hashtag campaigns, how actors involved in these specific campaigns were able to exploit specific dynamics of Twitter and the broader media and political establishment to progress their hyper-partisan...