Dr. Risius research is funded with approximately $10.1m AUD by the Australian Department of Home Affairs, the Hong Kong Research Council, Facebook, the German Academic Exchange Service, UQ Start-Up Grants and Temple University Young Scholar Forum.

On The Fairness of Data-Driven Online Extremism Detection

Collaborators: Rocky Tong (University of Queensland), Kevin M. Blasiak (University of Queensland), Okan Aydinguel (Mannheim University)

Grant Scheme: UQ AI Student Internship, Summer Projects, 2022 - 2023 ($3k AUD)

Algorand Centre of Excellence - Sustainability Informatics for the Pacific (ACE-SIP)

Collaborators: Monash University, University of Queensland (ITEE, Mathematics and Physics, Agriculture and Food Sciences, Centre for Policy Futures, Australian Centre for Water and Environmental Biotechnology, Earth and Environmental Sciences), University of Sydney, Swinburne University, University of Hong Kong, Polytech University of Hong Kong, University of Fiji, and Climateworks

Grant scheme: Algorand Foundation - Algorand Centres of Excellence ($8.6m AUD)

ACE-SIP (Sustainability Informatics for the Pacific) is a multi-university team advancing blockchain research and education in environmental, governmental, and social sustainability in the Pacific Region.

For further information:

Automated Verification of Ethereum Smart-Contracts (AVESC)

Collaborators: Mark Utting, Naipeng Dong

Grant scheme: University of Queensland Cyber Initiative Strategic Research Seed Funding Application ($74k AUD)

Blockchains and smart contracts are a promising technology for distributed finance applications. The correctness of smart contracts is crucial, since their code is public, they cannot easily be updated, and bugs can lead to millions of dollars being lost. This project will investigate a new approach to verifying the correctness of smart contracts that goes all the way from high-level financial properties down to the correctness of the low-level blockchain bytecode that implements the smart contract. The verification process will use automated SMT solvers that do not require theorem prover expertise, so the resulting verification tools will be widely usable.

Empowering Users to Protect their Personal Privacy on Social Media

Collaborators: Reza Ghaiumy Anaraky, Annika Baumann, Bart Knijnenburg, Hanna Krasnova

Grant scheme: Discovery Early Career Researcher Award (DECRA) ($370k AUD)

This Information Systems project takes a bold approach aiming to finally overcome the paradoxical inertia of people who care about their privacy but do not protect it. This project integrates different psychological theories proposing a paradigm shift expecting to generate new knowledge in privacy research, which can currently neither explain nor provide means to overcome the vexing issue. Expected outcomes of the project include a privacy behaviour model (PIM), privacy training program and system design solutions. This should offer substantial benefits as it integrates privacy research and guides behavioural models beyond Information Systems, provide means to solve the paradox, guide legislation and the privacy consent mechanism design.

Dynamic Matrix of Extremisms and Terrorism (DMET): A Continuum Approach Towards Identifying Different Degrees of Extremisms

Collaborators: Marten Risius, Kevin M. Blasiak, Susilo Wibisono, Rita Jabri-Markwell and Winnifred Louis

Grant scheme: Global Internet Forum to Counter Terrorism ($5k AUD)

We help expand GIFCT’s hash sharing database by proposing to extend the current binary understanding of terrorism (versus non-terrorism) with a Dynamic Matrix of Extremisms and Terrorism (DMET). DMET considers the whole ecosystem of content and actors that can contribute to a continuum of extremism (e.g., right wing, left-wing, religious, separatist, single-issue). It organizes levels of extremisms by varying degrees of ideological engagement and the presence of violence identified (e.g., partisan, fringe, violent extremism, terrorism) based on cognitive and behavioral cues and group dynamics. DMET is globally applicable due to its comprehensive conceptualization of the levels of extremisms. It is also dynamic, enabling iterative mapping with the region and time-specific classifications of extremist actors. Once global actors recognize DMET types and their distinct characteristics, they can comprehensively analyze the profiles of extremist actors (e.g., individuals, groups, movements), track these respective actors and their activities (e.g., social media content) over time, and launch targeted counter activities (e.g., de-platforming, content moderation, or redirects to targeted CVE narratives).

Combatting Cyberterrorism

Collaborator: Kevin Blasiak

Grant scheme: University of Queensland Start-up Grant ($20k AUD)

Terrorist and violent extremist use of the internet poses a major threat for modern democracies. In the Christchurch Call to Action, 48 countries committed to "bring together countries and tech companies in an attempt to bring to an end the ability to use social media to organise and promote terrorism and violent extremism" (Jacinda Ardern & Emmanuel Macron, 2019). We pursue the vision of combatting cyberterrorism through means of regulation and technology. We initially intend to focus on the following objectives & steps to achieve our long-term vision: (1) Introduce us to the field by engaging with key stakeholder groups, (2) Establish UQ as entity, actively conducting Cyberterrorism research, (3) Introduce and establish Cyberterrorism in the IS discipline, (4) Extend impact and engagement to develop capabilities for larger grants , and (5) Become a leading voice in informing global regulation and technological counter measures.

Privacy and Data Use

Collaborators: Reza Ghaiumy Anaraky, Bart Knijnenburg
Grant Scheme
: Facebook PhD Fellowship, Facebook Research ($90k USD)

Reza received a two-year Facebook PhD fellowship to support his work on privacy and data use. He focuses on empowering minorities and older adult populations to manage their online privacy as these groups are currently less attended in academic literature and industry.

For further information:

Political Bots in Social Media: Behaviour and Impact Analysis

Collaborator: Bikesh Upreti

Grant scheme: University of Queensland Start-up Grant ($20k AUD)

When the news on Cambridge Analytics’ social media data harvesting for political consulting[1] surfaced, it sent a shock wave around the globe. This project aims to contribute in two folds; political bots identify and understand these bots’ behavior and impact in political discourse. During the early stage, the project aims at developing a model capable of identifying the political bots active on Twitter. This work encompasses a systematic review of existing literature and news media to develop a comprehensive definition of bots, collect data, label data, and develop the prediction algorithm. During the second phase, once the bots are identified, the project builds on these identified bots. It aims to conduct a longitudinal study to understand the Bot activity, their interaction with users, and their role in influencing public opinion.

AI versus Human Fact Checkers: Do Trust and Reputation Affect the Spread of Fake News?

Collaborators: Guohou Shan, Jason Thatcher, Sunil Wattal

Grant scheme: Temple University Young Scholars Award ($1k USD)

This research helps inform platform providers on the implications of fact-checking by humans vs. AI on user engagement with content and enriches platform providers’ understanding of the effect of poster reputation in stopping fake news.

Terrorist and Violent Extremist Use of the Internet, Including Social Media Platform Services and Tools

Collaborators: Winnifred Louis, Susilo Wibisono, Kevin Blasiak

Grant scheme: Australian Government Department of Home Affairs ($60k AUD)

Terrorist and violent extremist use of internet platforms and social media is a major threat for modern democracies. While online networks provide virtually unlimited opportunities to connect and communicate with other people, they also promote the unilateral consumption of information that is similar to already held views, facilitate the propagation of fake news and ultimately the polarization of opinions. Social media campaigns that divide the public and radicalize individuals are becoming increasingly common approaches to interference with international and domestic issues. We are pursuing a research program in which we address these societal issues of social media technologies.

Cybermobbing on Social Media

The Role of Technology in Formation, Prevention, and Intervention of Online Collective Deviant Behavior

Collaborators: Christy Cheung, Jason Thatcher, Xiao-Liang Shen

Grant scheme: Hong Kong Research Grants Council, Senior Research Fellow Scheme ($1.3m AUD)

Our project aims to study the collective nature and mechanism of cybermobbing on social media and evaluate technology-based prevention and intervention strategies. In the first phase, we scrutinize the underlying collective nature of cybermobbing (online collective deviant behaviors) and examine how socio-technical factors (i.e., influences of other social media users, anonymous interactions, and disinformation tactics on social media platforms) affect cybermobbing on social media. In the second phase, we identify technology-based prevention and intervention strategies and examine their effectiveness for cybermobbing on social media.

Understanding Blockchain Affordances

Collaborator: Kai Spohrer

Grant scheme: German Academic Exchange Service (DAAD) ($47k AUD)

We have developed a joint research agenda on blockchain platforms and their distinctive properties. We plan to complete this research during the next two and a half years. Specifically, we aim to answer the research questions:

RQ1: What are the market mechanisms specific to blockchain platforms that influence their value, specifically in the form of cryptocurrency prices?

RQ2: What are the general affordances of blockchain platforms for service providers

RQ3: How do service providers respond to the different affordances of distinct blockchain platforms under development?

RQ4: Which consequences do hard forks have for blockchain platforms and their ecosystems?

RQ5: How do service providers on a blockchain safeguard against hard forks?