PhD Scholarship in Effective and Efficient Situation Awareness in Big Social Media Data

An ARC funded discovery project on the big social media analysis and management. Develop new solutions for applications in disaster management and decision making.

Situation awareness helps understand the elements in the environment, the current situation, and project the future actions. Real applications like crisis management require the real-time awareness of the critical situations. However, the services using traditional methods like phone calls can be easily delayed due to busy lines, transfer delays or limited communication ability in the disaster area. Social media-based situation awareness provides another feasible channel for crisis management, since critical events that cause loss of life are commonly identified in social media. For instance, during the Queensland floods in 2010-11, the central Burnett towns saw major flooding on 28-29 Dec, while Toowoomba became the major flood district after 10 Jan. 35 people lost their lives in the flood, and the cost to the Australian economy was over $10 billion. The crisis management personnel keep their situation awareness systems running for fast response to crisis. However, social media-based situation awareness must deal with a number of challenges related to big data and complex crisis events. 

This project aims to develop advanced techniques to analyse big social media data and more efficiently conduct critical situation awareness over online services. By enhancing the services and capabilities of crisis management users and reducing the loss in disasters, significant economic and social benefits will be brought to government, society, enterprises and social users. The PhD candidate will:

  • Develop effective strategies to manage large-scale social media data for complex crisis event detection and recommendation
  • Apply big data processing framework and design resource allocation and monitoring techniques to enable the human real-time situation awareness
  • Develop a workable system that will be employed as a showcase for complex social event detection and recommendation in situation awareness systems.

The scholarship is valued at up to $31,000 per annum for three years. Tuition fee will be waived by the university.

  • A first-class Honours degree or Masters degree in computer science with a major thesis component
  • Ranked in the top 10% in your class at a reputable national university or
  • Ranked in the top 30% of your class at a top 100 research university by world standards
  • Research background on social media analysis, recommender systems, database system or data mining areas
  • Meet RMIT University’s entry requirements for the Higher Degree by Research programs.

To apply, please submit your curriculum vitae and academic transcripts via email to Dr. Xiangmin Zhou via xiangmin.zhou@rmit.edu.au

Prospective candidates will be required to submit an application for admission to the PhD Computer Science program (DR221) as per instructions available on the HDR How to Apply website.

Scholarship applications will only be successful if prospective candidates are provided with an offer for admission.

Applications are open now.

Applications will close once candidates are appointed.

Having the following is desirable: a personal recommendation describing your research abilities from someone known by the supervisors, or a well-known research leader in a closely related field.

This scholarship will be governed by RMIT University's Research Scholarship Terms and Conditions.

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Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Luwaytini' by Mark Cleaver, Palawa.