Title: SH19: Modelling beliefs dynamics of social media users with machine learning methodologies
Funding: A full Home/EU fee waiver or equivalent fee discount for international students (£4,630 in 2019-20) (further fee details)
Application deadline: 28 June 2019
Start date: October 2019
Duration: 3 years (full time)
Location: Colchester Campus
Machine learning offers powerful tools to understand, predict and hopefully ameliorate the diffusion and effects of toxic content on social media that is recently having a high impact on our society.
This PhD scholarship is part of the research project “COURAGE: A Social Media Companion Safeguarding and Educating Students”, which is an international collaboration funded by VolkswagenStiftung (Volkswagen Foundation) as part of the Artificial Intelligence and the Society of the Future funding initiative. The project partners include the Universitat Pompeu Fabra (Spain), the Istituto per le Tecnologie Didattiche of the National Council of Research ITD-CNR (Italy), Hochschule Ruhr West (Germany) and the Rhine-Ruhr Institute for System Innovation (Germany).
The project aims to develop a Virtual Social Media Companion that educates and supports teenage school students facing the threats of social media such as discrimination and biases as well as hate speech, bullying, fake news and other toxic content. The companion will raise awareness of potential threats in social media among students without being intrusive. It will apply gamification strategies and educative information selection algorithms.
The Essex team will be involved in developing Bayesian computational models of beliefs dynamics of social media users to support governance and educational strategies. These models will also be applied to evaluate socially relevant variables, such as trust and inclusion. We will build on and implement state-of-the-art NLP & AI methods to provide measurements of sentiment, bias, hatefulness, veracity, polarisation, and sensationalism of social media content.
In addition, we will drive forward the state of the art in detecting hate speech and biased content. The companion will actively counteract this kind of content, balancing it with opposite perspectives and proposing specifically themed challenges adopting ideas used in games.
The PhD studentship aims to address these challenges combining dynamic network modelling with automated content analyses (textual or multimedia) using modern machine learning methods, such as Deep Learning and Hierarchical Bayesian Models.
The student may extract relevant content features, topics and events from online discussions to (a) predict short and long term responses of multiple users, (b) estimate the different effects of diverse information suggestion strategies in such context, and (c) define different interventions to improve model accuracy.
As such, we are particularly interested in PhD candidates that like to work on one or multiple of the following topics:
The successful applicant will join the Essex COURAGE team — formed by Professor Udo Kruschwitz (PI), Dr Dimitri Ognibene (Co-I) and Dr Aline Villavicencio (Co-I).
A full Home/EU fee waiver or equivalent fee discount for international students (£4,630 in 2019-20). International students will need to pay the balance of their fees (further fee details).
A doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,009 in 2019-20), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.
At a minimum, the successful applicant will have a good honours BSc degree (1st class or high 2:1, or equivalent) in computer science or related subjects. An MSc with Merit or Distinction is desirable (but not essential for students with a first class degree).
Strong analytical and mathematical skills are required, as well as good programming skills.
This role requires the following capabilities:
Understanding and/or experience in/of:
You can apply for this postgraduate research opportunity online.
Please include your CV, covering letter, personal statement, and transcripts of UG and Masters degrees in your application.
The University has moved to requiring only one reference for PhD applications and these can be received after a conditional offer has been made so the absence of these will not hold up the recruitment process.
Instruction to applicants
When you apply online you will be prompted to fill out several boxes in the form:
If you have any informal queries about this opportunity please email the supervisor, Dr Dimitri Ognibene (firstname.lastname@example.org)