Research at Underlined
Thesis & Research
Research at Underlined
Across disciplines, there’s a demand for people with a passion for crunching numbers. Vast amounts of new information and data are generated everyday through economic, academic, and social activities, much with significant potential economic and societal value. Techniques such as text and data mining and analytics are required to exploit this potential.
Today hospitals are using in-depth statistics to do predictive modeling, identifying opportunities to intervene early, for example. Education officials analyze test results and grade trends to improve student performance. Universities are measuring the student experience during the entire student journey to optimize the student experience with the help of data. And credit card companies and financial institutions ferret out risks and fraud.
“Each graduation project combines the two unique aspects: data science and entrepreneurship, meaning the graduation project is related to data, supported by a dataset, and has business or societal impact.”
Thesis assignments at Underlined
A hearty dose of math
In-depth statistics typically involve a hearty dose of math and computer science or programming, with opportunities for business of all branches. Throughout the year several Master students start their thesis assignments at Underlined. Each graduation project combines the two unique aspects: data science and entrepreneurship, meaning the graduation project is related to data, supported by a dataset, and has business or societal impact.
Examples Student Thesis & Research
- Measuring brand reputation through text-mining,
- Measuring consumers’ emotions through text-analytics of social media messages,
- Researching supervised machine learning techniques that can be used best for an optimal classification of CX data,
- Researching which modelling technique can be best used to determine the key drivers of the Net Promoter Score,
- Researching if Transfer Learning, applied to a small set of annotated data, can be a solution for domain- specific Aspect Based Sentiment Analysis.
Student’s Journey at Underlined
Making a lasting impact
Students have an active role in the application and elaboration of our (product) development in the field of CX, data and text mining. Developing text mining models, optimizing text mining algorithms, performing quality checks on models and algorithms, and testing our API products.
- Doing literature research to become an expert,
- Training, tutoring and guidance from professionals in the field,
- Applying techniques on actual customer datasets to put knowledge into practice,
- Comparing techniques and providing advise to improve business,
- Implementing techniques to make a lasting impact.
The research collection
Underlined makes theses accessible online worldwide. In the catalogue you can find (older) student theses of which a digital version is added to the collection.
- Welke modeltechniek kan het beste gebruikt worden om de belangrijkste drivers te vinden van de Net Promoter Score?
Author: Stance Lammers, Publication: 2021
- Welke supervised machine learning techniek kan het beste worden gebruikt voor een optimale classificatie van CX data?
Author: Fenna Blom, Publication: 2021
- Predicting the occurrence of complaints within the customer journey based on process mining techniques
Author: Jasper Nooyen, Publication: 2020
- Masterthesis Consumers’ Brand Image and Positioning Perceptions on Social Media
Author: Gerdien Ridderbos, Publication: 2015
- Masterthesis Sponsoring via Social Media
Author: Bart Smarius, Publication: 2012
- Masterthesis Social Sentiment als voorspeller van NPS
Author: Hanneke van Keep, Publication: 2012