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Research Thesis Topic

Sentiment Analysis for Detection of Depressive Users on Social Networks


Topic ID
226

Thesis Topic/Title
Sentiment Analysis for Detection of Depressive Users on Social Networks

Description

Many people are suffering from depression without knowledge of it. As a result, they are unable to access to appropriate helps. Finding and helping such depressive people have motivated us in the work proposed in this thesis project, which will evaluate users' expressions on social networks and alert potential depression adopting the techniques in natural language processing, text mining and sentiment analysis. With the outcome of the work, social workers can find depressive people and deliver help to them efficiently; guardians like parents can have an eye on their children's psychological conditions closely; people suffering from minor depression can monitor their psychological conditions easily, so that they could pull back at early stage and avoid falling into more severe circumstances if anything wrong is happening. The proposed thesis will make potential theoretical contributions to understandings of depression on social networks, as well methodological contributions to text mining and sentiment analysis.


Principal Supervisor

Associate Supervisors

Research Affiliations
  • School of Agricultural, Computational and Environmental Sciences

Field of Research
  • Artificial Intelligence and Image Processing
  • Information Systems
  • Other Psychology and Cognitive Sciences
  • Public Health and Health Services


Application Open Date
15/08/2016

Application Close Date
15/08/2020

USQ Scholarship Applications

Pre-approved for Ethics
Not Applicable

Admission Requirements

Please review the admission requirements for the academic program associated with this Thesis Topic

Programming skills
Database skills
Communication skills
NO requirements for psychological background




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