Deep Learning for Detecting Fake News

Novel Deep Learning Approaches for Detecting Fake News

Degree type

MRes/PhD

Closing date

10 October 2022

Campus

Launceston

Citizenship requirement

Domestic/International

About the research project

Online Social Networks have shaped the digital world to such an extent that they have now become an indispensable part of life for most of us. Rapid and extensive adoption of online services is influencing and changing how we access information for decision making. One of the main advantages and attractions of social media is the fact that it is fast and free (mostly). Meanwhile, the ease of producing and distributing news through social media has also simultaneously sharply increased the widespread of fake news. In a recent study, it has been found that nearly 50 percent of traffic taken from Facebook are largely fake, while at the same time, news publishers rely on Facebook for at least 20 percent of their traffic. Fake news threatens multiple spheres of life and can bring devastation not only to economic and political aspects but also peoples' wellbeing and lives.

This project involves developing new deep learning algorithms to learn and discover patterns in online news datasets, that can then be used to detect fake news. This requires developing new Deep Neural Network (DNN) algorithms for natural language processing. DNNs have increasingly been employed to handle AI applications such as natural language processing with some success, however, certain significant issues remain unresolved. Such issues include dataset bias and imbalanced data distribution, optimal DNN parameter set, and Multimodal effect. In this project, you will develop new DNN algorithms to overcome these and possibly other issues for faster, more reliable, and more accurate fake news detection.

Primary Supervisor

Meet Dr Shuxiang Xu

Funding

Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

  • a living allowance stipend of $28,854 per annum (2022 rate, indexed annually) for 3.5 years
  • a relocation allowance of up to $2,000
  • a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.

Eligibility

Applicants should review the Higher Degree by Research minimum entry requirements.

Additional eligibility criteria specific to this project/scholarship:

  • Applications are open to Domestic/ International/ Onshore applicants
  • Applicants must be able to undertake the project on-campus

Selection Criteria

The project is competitively assessed and awarded.  Selection is based on academic merit and suitability to the project as determined by the College.

Application process

There is a three-step application process:

  1. Select your project, and check you meet the eligibility and selection criteria;
  2. Contact the Primary Supervisor, Dr Shuxiang Xu to discuss your suitability and the project's requirements; and
  3. Submit an application by the closing date listed above.
    • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
    • As part of your application, you will be required to submit a covering letter, a CV including 2 x referees and your project research proposal.

Following the application closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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