In the ReEntrust project, we aim at rebuilding users’ trust on online platforms after a breakdown. In order to achieve this goal, we first have to (1) identify the elements that generate these breakdowns, (2) analyse the effect of several factors such as digital literacy or age range in these processes and (3) gather valuable data on the mental patterns that a user goes through when using these platforms.
We first chose to focus on recommender systems applied to the particular case of hotel booking. Thus, we designed a fake (but realistic) booking website where users were told to book a hotel room in Paris within a designed budget and for a specific date.
However, the fake booking website contained several trust-breaking features:
- Pressure selling: The number of hotel rooms available is decreasing rapidly and discounts have timers.
- Hidden charges: The price displayed does not include the platform tax.
- Bad behavior: The hotels displayed will show the “featured hotels” first.
- False claims: The discount will not be applicable.
- Discrimination: The website will prompt that you will not be able to afford the trip.
- Unrealistic prices: The breakfast will be highly overpriced.
The git repository is accessible online on my github page.