About the Project
Project summary:
Social media such as Twitter is being increasingly exploited for the propagation of hate speech and the organisation of hate based activities. The UK has seen significant increase of hate speech on social media towards the migrant and Muslim communities following events including leaving the EU, the murder of MP Jo Cox, the Manchester/London attacks, leading to record spikes of hate crimes and threats to public safety due to cases of inciting hate crimes. Rising hate speech and related crime are also reported in the US since election, and the EU (80% of young people have encountered hate speech online and 40% felt attacked or threatened).
The project will investigate, and develop data analytics methods and technologies to effectively combat such issues by detecting and tracking the emergence and spreading of hate speech on social media, and ultimately support humans in timely detection of emerging threats to the public and decision making for intervention. This will involve large scale data gathering through social media platforms, development of novel methods of Machine Learning, Natural Language Processing (NLP), and Information Extraction (IE), for automated real-time detection and analysis of hate speech on Twitter.
The project is an excellent opportunity to develop highly sought-after knowledge, skills and experience in cutting-edge technology with strong support from a professional research team led by academics renowned for their work in the relevant fields. You will gain knowledge and skills in the areas of Big Data analytics, machine learning and natural language processing, which are highly desired by the data science industry. You will receive excellent facility support including access to the University HPC computing cluster, and ample opportunities to receive support from vibrant research/PGR community within the School and the University, and developing your professional network by attending various prestigious academic conferences and technology showcase events.
Specific qualifications/subject areas required of the applicants for this project:
Entrants must have a first/undergraduate Honours degree, with an Upper Second Class or a First Class grade, in Computer Science. Entrants with a Lower Second Class grade at first degree must also have a postgraduate Masters Degree at Merit.
Essential: strong math and programming skills (Java or Python is preferred to C++); strong analytical and creative thinking skills; good communication skills and ability to work both in team and independently; experience of report-writing; interest in the above mentioned subject areas; being a fast learner with ‘can do’ attitude and strong commitment; effective planning and time management; willingness to publish and present findings at conferences; willingness to travel given available funding.
Desirable: experience and knowledge of code management and build tools such as GitHub, Apache Maven; experience of undertaking research; knowledge of machine learning, natural language processing, statistics, and social media platform APIs; knowledge of JavaScript and Web development
Interviews are likely to take place on the following dates: 15/01/2018 to 19/01/2018
This studentship competition is open to applicants who wish to study for a PhD on a full-time basis only. The studentship will pay UK/EU fees (currently set at £4,195 for 2017/18 and are revised annually) and provide a maintenance stipend linked to the RCUK rate (this is revised annually and is currently set at £14,553 for the academic year 2017/18) for up to three years. Applications from non-EU students are welcome, but a successful non-EU candidate would be responsible for paying the difference between non-EU and UK/EU fees. (Fees for 2017/18 are £12,900 for non-EU students and £4,195 for UK/EU students). The studentships will be expected to commence in October 2018.