Real-time Extensible English Language Racism Monitor and Research Tool
People
Description
2021 Project - Call for Expression of Interest
- 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
- A one paragraph description of yourself, including also reference to the subject you would be enrolled in if doing the project.
- A one to two paragraph description of the contribution you would envisage making to the project, including prior experience relevant to the proposed contribution.
- A copy of your cv and academic transcript.
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". https://contractfortheweb.org/ 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.
Background Literature
Eugenia Siapera, Elena Moreo, Jiang Zhou. Hate Track Tracking And Monitoring Racist Speech Online
https://www.ihrec.ie/app/uploads/2018/11/HateTrack-Tracking-and-Monitoring-Racist-Hate-Speech-Online.pdf
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
https://www.tandfonline.com/doi/full/10.1080/00131857.2019.1602891
Karsten Muller and Carlo Schwarz, Fanning the Flames of Hate: Social Media and Hate Crime
https://www.researchgate.net/publication/321959002_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
https://www.isdglobal.org/wp-content/uploads/2019/07/The-Great-Replacement-The-Violent-Consequences-of-Mainstreamed-Extremism-by-ISD.pdf
Joint open letter on concerns about the global increase in hate speech (25 UN human rights rapporteurs and experts)
https://www.ohchr.org/en/NewsEvents/Pages/DisplayNews.aspx?NewsID=25036&LangID=E
RESEARCH PAPER Hate Speech Detection Using Natural Language Processing Techniques Author Shanita Biere Supervisor Prof. dr. Sandjai Bhulai Master Business Analytics
beta.vu.nl
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Requiem for online harassers: Identifying racism from political tweets
https://ieeexplore.ieee.org/abstract/document/7962526
Requiem for online harassers: Identifying racism from political tweets - IEEE Conference Publication
During the last five years, the amount of users of online social networks has increased exponentially. With the growing of users, social problems also aris
ieeexplore.ieee.org
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gradient-boostingdecisiontrees(GBDTs).ForthelaŠer,theyfirst traintheLSTMonthetrainingdata,andthenusetheaverageofthe wordembeddingslearnedbytheLSTMastheinputfortheGBDT.
arxiv.org
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Multilingual Cross-domain Perspectives on Online Hate Speech https://arxiv.org/ftp/arxiv/papers/1809/1809.03944.pdf
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Mining communities and their relationships in blogs: A study of online hate groups
https://www.sciencedirect.com/science/article/abs/pii/S1071581906001248
Platformed racism: The mediation and circulation of an Australian race-based controversy on Twitter, Facebook and YouTube
http://eprints.qut.edu.au/101370/
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Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
http://www.aclweb.org/anthology/N16-2013
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eprints.qut.edu.au
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Abstract. This paper uses centrality measures from complex networks to discuss how to destabilize terrorist networks. We propose newly introduced algorithms for constructing hierarchy of covert networks, so that investigators can view the structure of terrorist networks / non-hierarchical organizations, in order to destabilize the adversaries.
link.springer.com
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A Unified Deep Learning Architecture for Abuse Detection
https://arxiv.org/abs/1802.00385
Abstract: Hate speech, offensive language, sexism, racism and other types of abusive behavior have become a common phenomenon in many online social media platforms. In recent years, such diverse abusive behaviors have been manifesting with increased frequency and levels of intensity. This is due to the openness and willingness of popular media platforms, such as Twitter and Facebook, to host ...
arxiv.org
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Deep Learning for Hate Speech Detection in Tweets https://dl.acm.org/citation.cfm?id=3054223
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Cyberbullying Detection and Classification Using Information Retrieval Algorithm
https://dl.acm.org/citation.cfm?id=2743085
Social media and digital technology use among Indigenous young people in Australia: a literature review https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881203/
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academic.csuohio.edu
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law.unimelb.edu.au
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researchonline.jcu.edu.au
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