The project will aim to help the UK Statistics Authority (UKSA) efficiently extract key terms and information from the Look to the Future survey .
- Stuart Newcombe
- David Pugh
Impact (see the impact assessment framework for further details)
Which of the Campus strategic objectives would this project deliver, and how?
- Helpful - strengthen evidence for policy making
What is the policy impact? Why is this project important?
- Will help UKSA quickly understand key responses to help drive workshops and meetings within hours of survey ending
What is the technical impact?
- The project will use simple NLP techniques such as TF-IDF and topic modelling, reusing the Campus PyGrams tool.
- The project will aim to help DIT quickly analyse the MFN consultation
- Project will start as the consultation launches in February
- Data source will be MFN Consultation responses. Until the consultation closes it is unknown the quantity and quality of these responses. Data will have all identifying and protected characteristic information removed and should be treated as official sensitive.
- It is uncertain what quantity and quality of data is expected. The consultation question structure could lead to a very sparse dataset with short responses, and will only be . The ability to apply any techniques will be very dependent on the data collected. Resource at DIT could also be reassigned with little notice.
Code and outputs
- Example code handed to DIT for use on their system
Related and existing work
- January 2020 Survey closes
- January 2020 Analysis delivered
Please contact email@example.com for more information.
- No updates yet.