Publicação
Enhancing trust, fairness, and performance in the sharing economy-algorithmic bias in the sharing economy: examining visibility disparities in Airbnb’s recommendation system
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | |
| dc.contributor.advisor | Guha, Sreyaa | |
| dc.contributor.author | Cortes, Joaquim Albuquerque Dorey | |
| dc.date.accessioned | 2026-04-08T13:10:50Z | |
| dc.date.available | 2026-04-08T13:10:50Z | |
| dc.date.issued | 2025-01-20 | |
| dc.date.submitted | 2024-12-17 | |
| dc.description.abstract | This work project explores the factors shaping Airbnb host performance, visibility, and guest sentiment, focusing on algorithmic dynamics and predictive analytics. Using diverse datasets and Machine Learning models, it uncovers how Airbnb’s recommendation system impacts trust, competitiveness, and guest engagement. Key findings reveal that review volume and host responsiveness drive performance, with smaller hosts facing challenges in visibility and pricing. Sentiment analysis highlights the outsized impact of negative reviews on reputations. The study identifies biases in Airbnb’s algorithms, emphasizing the need for fairness, transparency, and user feedback to ensure equitable opportunities for all hosts in the sharing economy. | eng |
| dc.identifier.tid | 204133610 | |
| dc.identifier.uri | http://hdl.handle.net/10362/202106 | |
| dc.language.iso | eng | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Airbnb | |
| dc.subject | Machine learning | |
| dc.subject | Guest sentiment | |
| dc.subject | Algorithmic bias | |
| dc.subject | Host visibility | |
| dc.subject | Sharing economy | |
| dc.subject | Recommendation systems | |
| dc.subject | Review volume | |
| dc.subject | Predictive analytics | |
| dc.subject | Trust building | |
| dc.title | Enhancing trust, fairness, and performance in the sharing economy-algorithmic bias in the sharing economy: examining visibility disparities in Airbnb’s recommendation system | eng |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics |