Study level

Master of Philosophy


Vacation research experience scheme

Faculty/Lead unit

Science and Engineering Faculty

School of Information Systems

Topic status

We're looking for students to study this topic.


Dr Reihaneh Bidar
Associate Lecturer
Division / Faculty
Science and Engineering Faculty
Dr Renuka Sindhgatta Rajan
Lecturer Service Science
Division / Faculty
Science and Engineering Faculty


The purpose of this research is to provide a methodology to detect and mitigate destructive patterns that are generated in crowdsourcing systems which result in negative consequence through contributors’ interactions.

Vote manipulation is a form of co-destruction that can result from intentionally biasing a rating.

Our ultimate goal is to provide guidance when setting up crowdsourcing systems that prevents co- destruction or detects it before it becomes problematic.

Research activities

As a VRES student, you'll assist the research team by investigating real-life data sets.

As a research student (Honours or Masters) you may develop algorithms that provide a detection /mitigation mechanism for a particular co-destruction pattern in crowdsourcing systems. This could include GitHub or Wikipedia.


As a result of finishing this project, you'll need to:

  • extract a relevant information from a crowdsourcing platform.
  • provide an algorithm for detecting or mitigating a particular co-destruction pattern from occurring in crowdsourcing systems.

Skills and experience

To be considered for this project, you should have a technical background in:

  • computer science
  • information technology
  • data science
  • equivalent field of study.

You should also demonstrate excellent programming skills in Python.


Contact the supervisor for more information.