| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor.advisor | Corten, Rense | |
| dc.contributor.author | Zhang, Chenjun | |
| dc.date.accessioned | 2022-09-09T03:03:00Z | |
| dc.date.available | 2022-09-09T03:03:00Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/42674 | |
| dc.description.abstract | Online markets became progressively dominate in today’s society, accompanied with this wide spread of online market, online rating systems emerged. Online reviews and rating system can provide useful information for both the customers and the product or service suppliers. This project focused on the suppliers’ perspective towards the online reviews with data from a dutch website Werkspot.nl which provides plumber service. Implemented text mining and LDA topic model to the reviews, the project explored the concerns of the homeowners and subsequently proposed several methods that can help the professionals improve themselves to obtain high rating scores and more working opportunities. | |
| dc.description.sponsorship | Utrecht University | |
| dc.language.iso | EN | |
| dc.subject | Use topic modeling to find the topics from the online reviews, and then summarize the customer behavior so that the service suppliers can adjust themselves to improve work opportunities. | |
| dc.title | Topic Modeling and on online reviews | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.courseuu | Applied Data Science | |
| dc.thesis.id | 10154 | |
