Titulo Estágio
User Experience (UX) and opinion mining of technology-enabled solutions for health
Local do Estágio
DEI-FCTUC
Enquadramento
Over the last decade several text mining techniques have been applied in large textual dataset to help identifying relevant concepts, as well the relations between them. These automatic and semi-automatic methodologies have also been applied to identify opinions and sentiments from public fora. Focusing on the Human-Computer Interaction area, they have the potential to continuously monitor the users’ perception about technology and new systems, namely technology-enabled solutions for health, such as exergames and games for health.
This proposal is situated at the intersection of the following areas: Human-Computer Interaction and Text Mining (and health and fun). If you’re interested and/or skilled in one of these areas, this is the project for you!
Objetivo
The aim is to develop an opinion mining and sentimental analysis methodology, that helps better understanding how end-users perceive the added-value of new technologies, namely technology-enabled solutions for health, such as exergames and games for health.
Plano de Trabalhos - Semestre 1
Phase 1: Literature review and state of the art
Phase 2: Identification of the main resources from which user experience (UX) will be monitored – e.g. social media (e.g. Twitter, Facebook), digital magazines (e.g. Wired), blogs and forums (e.g. Reddit)
Phase 3: Definition of vocabularies with the main concepts (e.g. Wii, dance dance revolution, ..), as well desirable (e.g. satisfying, helpful, fun, ..) and undesirable (boring, unpleasant, ..) aspects that influence the UX
Phase 4: Development of a fully-fledged project proposal
Plano de Trabalhos - Semestre 2
Phase 5: Apply a text mining and relation extraction tool (e.g. GATE)
Phase 6: Validation and assessment of results
Phase 7: Dissertation write-up
Condições
Good proficiency in python/java programming is a relevant. Previous experience in information extraction and text mining is also a plus.
Observações
This work will be supervised by Dr Paula Alexandra Silva (paulasilva@dei.uc.pt) and co-supervised by professor Joel Arrais (jpa@dei.uc.pt).
Students are encouraged to send an email to the supervisors before applying for the project. Feel free to include your CV and state your skills in any of the following fields: Human-Computer Interaction Design, Text mining, and Machine Learning.
Orientador
Paula Alexandra Silva
paulasilva@dei.uc.pt 📩