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Research Background

On this page, we outline some of our research projects.

One core team research thread centers on our efforts to improve the methodology around the inclusion of social media text analysis (as an example of networked unstructured text analysis) in decision-support applications. The three problem spaces we are currently focusing on are:

  1. Drawing insights and knowledge from networked and unstructured data;
  2. Characterising the communities underlying social media insights to to understand what is usual or unusual community behaviour.
  3. Developing methodologies for reporting social media insights in decision support applications

These three problems are interconnected.  In Problem 1, we research methods to transform social media data into some insight.  In Problem 2, we research ways to understand which communities are represented in the sample used to generate the insight.  Finally in Problem 3, we research ways to present the insights and descriptions of the communities (touching on points of representative data) in the context of an application.

Through the projects below, we have made contributions in demonstrating:

  • the utility of social media data in supplementing other data sources for health analytics, supporting mental health research and supporting emergency situation awareness;
  • the use of social media data for estimating demographic characteristics
  • methodological insights about decision-support applications in the face of social media data biases

We are also interested in other research involving natural language processing, information retrieval, statistics, and social media analytics.  Please see the current projects below, or contact our team for more details.


Brochures/Webpages for Business:

Current Projects: