Real-time Extensible English Language Racism Monitor and Research Tool


Supervisory Chair



2021 Project - Call for Expression of Interest

Redeem: Real-time Extensible Design for English-language Evaluation and Monitoring of online racism and associated research tools
In 2021 this project will be focussed on building a software application providing an online research tool for evaluating and monitoring online racism. This project is suitable for undergraduate and coursework Masters students undertaking a one semester. The project will seek to create an extensible tool for the monitoring of online racist chatter. The tool will consist of a number of software units and associated interfaces with the aim of providing a public facing racism monitoring tool and a firewall protected researcher web tool. 
Students may contribute to the project by contributing to software development for one or more of the units, by contributing to requirements and feasibility analysis and/or by contributing to development of detailed software specifications. 
Currently units for the project would include:
  • A data input unit which will return 'statement' objects enhanced with relevant metadata
  • A data pre-processing and classification unit which will prepare data for classification and return a classification (e.g. return a classification of statements as racist or not-racist) 
  • A machine learning unit that will assist the data processing and classification unit with classification
  • A database for storing data necessary for functionality of the research tool 
  • A time series unit which will undertake time series related tasks such as representation of a series of statements as a time series and which will provide time series analysis tools (e.g. spikes and discontinuities), and visualisation
  • A geographic unit which will enable visualisation of statements in both time and in terms of a geographic visualisation
  • A web-based visualisation unit that will enable interactive visualisation of data in both real-time and over specified periods
  • A web-based firewall protected research tool for racism researchers focussing on fine grained investigation of racist content and providing natural language - corpus, concordance and similar tools
Software development should be primarily in Python. Javascript may be suitable for client-side scripting for web-based interfaces. Database development will likely be in sql. All code will need to be accompanied by documentation and testing framework. Software and data design should ensure anonymity but allow for the influence of deidentified "actors" to be analysed.
The document at the following link, provides an outline visual description of project requirements
To submit an expression of interest please write to Expressions of interest should be received by no later than 30 January 2021 for a Semester 1 project and no later than 10 July 2021 for a Semester 2 project. Successful applicants for Semester 1 will be notified by 7 February 2021 and 19 July 2021 for Semester 2. Expressions of Interest should include:
  1. A one paragraph description of yourself, including also reference to the subject you would be enrolled in if doing the project.
  2. A one to two paragraph description of the contribution you would envisage making to the project, including prior experience relevant to the proposed contribution.
  3. A copy of your cv and academic transcript.
Note that a condition of your participation in this project is that you agree to grant a licence to the project to continuing use and adaptation of any intellectual property you contribute.

Broader Goals and Description of this Project

This project seeks to apply and/or advance the state of the art in computer science in the detection and prevention of use of information technology for racist purposes and for the purpose of developing and demonstrating computational tools for the study of racism, particularly in application to online data. The project may involve basic research, applied research or a combination of both. It is likely that existing methods addressing other online threats will be relevant to the problem domain including methods to address online misogyny, bullying, terrorist networks and their identification and disruption (as examples). The project is likely to involve use of natural language processing, machine learning and network analysis as existing technologies deployed in this problem domain. 


The project may involve working with government and non-government external stakeholders concerned with the problem of online racism to assist them in responding to online racism.  Research by publication is encouraged as part of this project.


Dr Michael Curtotti will be the primary supervisor for this project and would provide the main source of supervision during the project.  Dr Eric McCreath would also provide some supervisory direction and act as the chair for the panel of supervisors.  If you are interested in this project in the first instance please contact Michael.


Previous Student Projects

  • Racism Detection by using BERT-Based Transfer Learning Approach in Twitter. Zixin Wang (COMP4560 Advanced Computing Projects - 2020 Semester 2)
  • The Detection and Prediction of Trigger Events in Racist Chatter in Twitter Streams. Erin Qin (ENGN2706 Research Methods – 2020 Semester 1)
  • Sentiment Analysis and Mapping of the “White Australia” Concept in Australian Newspaper Archives. Angus Wickham  (COMP4560 Advanced Computing Projects – 2020 Semesters 1 & 2)

Some Background


In November 2018 the founder of the world wide web, Tim Berners Lee launched a campaign to "save the web". The campaign called on institutional and individual users of the web to sign on to a "Contract for the Web".  The background of the launch was the misuse of the web for purposes never intended by its founders. Among these is the propagation of racism (including online racist bullying), which is typically a violation of the terms of use associated with the internet and services provided via the internet. Among the principles of the contract for the web were an undertaking by companies to:


  • Develop technologies that support the best in humanity and challenge the worst
  • So the web really is a public good that puts people first.
And an undertaking by individuals to Build strong communities that respect civil discourse and human dignity So that everyone feels safe and welcome online.
The propagation of racism through the internet and other information technologies at its worst represents a threat to democratic institutions. It directly impacts and harms individuals and communities targeted by online racism and often harms the well-being of those who are recruited into racist networks. Political movements seeking to establish or re-establish preferential treatment on the basis of race or exploit racist sentiment for political purposes use information technology to propagate their messages. Such movements have demonstrated their ability to affect overall societal trends. Companies such as Facebook and Twitter have been criticised for their inadequate response to the use of their platforms for racist purposes and in other ways which bully or harass individuals and communities. 
Within Australia, racist messages take on a particular character, sometimes directed against indigenous Australians (who are among those most impacted by online racism) and recent migrants. Debates concerning contested social issues such as immigration or crime are exploited to promote racist ideas and attitudes. Sometimes the Australian context consciously or unconsciously absorbs racist ideas from broader global discourse. Some racist discourse is generated by media coverage and political figures. In 2018 racist networks were alleged to have infiltrated a major Australian political party (the Nationals). The networks were identified by investigative journalism  
Outline of Some Potential Research Issues
The detection of and response to racism in online environments is a growing field of research. Beyond detection and description of racism is the development of effective mechanisms to impede the spread of racism in online fora. Information technology can also be used in a positive sense. Racist discourse is of course generated by human beings. Development of effective and objective measures for assessing whether particular speech is racist (or has racist impacts) is a philosophical, linguistic and computational problem that would benefit from research and attention. Any appropriate addressing of such issues must be based on an understanding of the boundaries of appropriate free speech in a democracy and how appropriate speech can be distinguished from speech which directly or indirectly has a racist content or impact. Inevitably research in this area must also begin from a theory of the nature and character of racism.  As an example of problems in the domain, research in 2018 showed the fragility of existing machine learning methods to simple strategies for evading detection. Researchers involved also noted the inherent subjectivity of training datasets for what constitutes "hate speech". ( Detection moreover is of limited value if tools do not exist to respond to disrupt/interdict online harassment. A key problem in that respect is the identification of online abusers who are motivated to seek to evade detection (e.g. taking advantage of the anonymity of the web). 
Examples of existing research that relates to this project are linked below.
We are seeking expressions of interest from students who may be interested in undertaking research at the Masters or PhD level, related to the issues outlined above.  Students would be supported by a multidisciplinary team of supervisors. Students undertaking senior level undergraduate projects will also be considered.


Background Literature

The following provides a list of selected materials demonstrating some of the existing research in this field.

Eugenia Siapera, Elena Moreo, Jiang Zhou. Hate Track Tracking And Monitoring Racist Speech Online

Tina Besley & Michael A. Peters (2019) Terrorism, trauma, tolerance: Bearing witness to white supremacist attack on Muslims in Christchurch, New Zealand, Educational Philosophy and Theory

Karsten Muller and Carlo Schwarz, Fanning the Flames of Hate: Social Media and Hate Crime

Jacob Davey and Julia Ebner (2019), The Great Replacement: The Violent Consequences of
Extremism, the Institute for Strategic Dialogue

Joint open letter on concerns about the global increase in hate speech  (25 UN human rights rapporteurs and experts)
Hate Speech Detection Using Natural Language Processing Techniques


Requiem for online harassers: Identifying racism from political tweets
All You Need is “Love”: Evading Hate Speech Detection

Multilingual Cross-domain Perspectives on Online Hate Speech





Mining communities and their relationships in blogs: A study of online hate groups
Blogs, often treated as the equivalence of online personal diaries, have become one of the fastest growing types of Web-based media. Everyone is free …




Platformed racism: The mediation and circulation of an Australian race-based controversy on Twitter, Facebook and YouTube





Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter

Proceedings of NAACL-HLT 2016, pages 88–93, San Diego, California, June 12-17, 2016. c 2016 Association for Computational Linguistics Hateful Symbols or Hateful People?
Matamoros-Fernandez, Ariadna < (2016) Platformed racism: The mediation and circulation of an Australian race-based controversy on Twitter, Facebook and YouTube. In Association of Internet Researchers Annual Conference (AoIR 2016), 5-8 October 2016, Berlin. (Unpublished)

Modeling Community Behavior through Semantic Analysis of Social Data: the Italian Hate Map Experience
Practical Algorithms for Destabilizing Terrorist Networks

A Unified Deep Learning Architecture for Abuse Detection






Deep Learning for Hate Speech Detection in Tweets
Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis.



Cyberbullying Detection and Classification Using Information Retrieval Algorithm
Social networking site is being rapidly increased in recent years, which provides platform to connect people all over the world and share their interests.




Social media and digital technology use among Indigenous young people in Australia: a literature review
The use of social media and digital technologies has grown rapidly in Australia and around the world, including among Indigenous young people who face social disadvantage. Given the potential to use social media for communication, providing information and as part of creating and responding to ...




Issues Surrounding Cyber-Safety for Indigenous Australians
Joint Select Committee on Cyber-Safety


Content Analysis KIMBERLY A. NEUENDORF and ANUP KUMAR Cleveland State University, USA Introduction ...
Alt_Right White Lite: trolling, hate speech and cyber racism on social media
2017] Regulating Cyber-Racism 3 Advance Copy deluge of online animosity that flooded their Facebook page.1 Goodes, a retired Australian Football League (‘AFL’) player, had already been the target
Racist violence in schools is on the documented increase worldwide. This paper will make the argument that the nature of and motivations for such attacks are changing as a function of the new electronic communication technologies available to students. The prevalence in school communities is thought to be under-represented due to the under-reporting of incidents to authorities.

Islamophobia and Twitter: A Typology of Online Hate Against Muslims on Social Media
Cyber bullying, cyber stalking, human rights violations online and related domains

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