Project Abstract

Online real estate marketplaces are unfair to consumers. Price hikes, psychological biases and misleading in-search ads are just some of the problems prospective buyers face. The current state of this market, with a near Oligopoly by the big corporations in the industry have lead to consumer autonomy being vastly reduced. Homes are inherently subjective and each one is unique. The current solutions do not focus on the subjective nature of the market instead focusing on profit. I present a proof of concept marketplace to battle these biases and give autonomy back to the buyer, while highlighting each properties unique value to a prospective buyer. Developed with a virtually threaded spring boot backend API, a reactive next.js front end as well as MongoDB and standard tools like docker and git. This tech stack allows me to serve requests rapidly with limited hardware, which is important when considering the vast number of houses which would need to be stored. At the current time data is seeded since it is a proof of concept, and other options are not viable for this project e.g. web scraping, high cost apis. This is more than just a dissertation though as I will attempt to later create aggregate data from trusted sources. Furthermore, providing the user with a priority based searching algorithm, allows the search criteria to really match the users desires, rather than a recommend systems best guess. This marketplace hides sources of bias initially such as prices, and instead focuses on what really matters. Data such as crime rates, features of the home, and images thereof. These changes allow home owners to focus on the real value of these homes, rather than the cost. Therefore improving the consumer’s experience in this market.

Keywords: Web Applications, Priority Algorithms, In The Market

 Conference Details

Session: A

Location: Sir Stanley Clarke Auditorium at 11:00 13:00

Markers: Casey Hopkins, Arno Pauly

Course: BSc Software Engineering 3yr FT

Future Plans: I’m looking for work