This project identifies how misunderstandings of harm and safety flow into flawed data logics and ineffective automated digital platform responses. To date, platforms have presented the principal unit of harm as individual pieces of content or media objects.

This project will evaluate the moderation of social media content, which has become radically more reliant on machine learning classifiers during the Covid-19 pandemic. We examine moderation at this time through two case studies, which aim to: 1. Test allegations of political bias in the removal of tweets, and 2.

The project maps the extent, qualities and diversity of conversations about automation and ADM in Australia and globally, using key social media data sources including Twitter and Facebook to collect posts and a wide range of media articles.

Automated agents, known as bots are widely used on the internet to run automated tasks. Whilst some bots are designed to perform beneficial activities, others are created for malicious purposes. The inauthentic coordination of bot activities is problematic and threatens to undermine online environments. We have very little understanding of how bots and high-volume accounts are policed and moderated by users themselves, and what drives people to create bots (both beneficial and malicious).

This project brings together qualitative domain expertise in digital media and platform studies with data science and machine learning to evaluate and improve attempts to detect and deal with problematic automated agents (bots) in social media. It addresses the question of how bots are moderated and perceived by the community, across platforms Twitter and Reddit.

The use of custom targeted advertising, known as ‘dark ads’ poses a host of potential social harms, from the re-introduction of historical forms of discriminating (targeting job or housing ads by race, for example, or job ads by race or gender, and so on); to the propagation of racist or gender stereotyping, to the spread of false and harmful information. The advertising environment is fundamentally transformed by the rise of dark ads, which continue the trend away from mass advertising, which was available to large audiences and thus subject to public scrutiny.