Development of a language evolution model using social media data.
What is happening on social media? Who is speaking to whom? The language of social media is rapidly evolving, but we don’t know how or why. The enormous quantities of data available from Twitter allow for a real-time investigation of the exchanges occurring on this platform. By focusing on specific elements of this data, such as hashtags, this project will quantify the rate of evolution, identify the drivers of this evolution, and develop a model for the language dynamics. This project will use information theory and techniques from machine learning and Natural Language Processing for the quantitative analysis.
This project is associated with the Centre for Translational Data Science (CTDS) Incubator grant "Extracting information from texts using stochastic block models", E. Altmann, M. Bednarek, T. Alexander. The successful project applicant will have the opportunity to work with researchers from across the University through the CTDS and may be eligible for supplementary funding.
Additional supervisor for this project is Associate Professor Monika Bednarek.
HDR Inherent Requirements
In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:
The opportunity ID for this research opportunity is 2691