Date of Award


Document Type

Thesis (Undergraduate)

Department or Program

Department of Computer Science

First Advisor

Lorie Loeb


Individuals use measures of reputation as heuristics for determining how much interest and trust they should place in other individuals. Clear measures of reputation save time and increase efficiency because they prevent individuals from having to go through the traditional process of determining reputation, especially in cases where these traditional measures no longer suffice. Repcoin aimed to give experts in different areas a platform for highlighting their expertise, provide an avenue for users to find credible experts in different areas, and a place for users to try and predict whose reputation will increase and thereby prove their ability to identify who will be credible in the future. Repcoin’s 300 users used the site on a regular basis and displayed complex behavior. Repcoin failed in its aim to function as a proof-of-concept for accurately storing and predicting future reputation, and didn’t provide a sufficient incentive for its users to display their content on the site. The Repcoin experiment illustrates the difficulties of building a simple but accurate market for reputation but shows that users are willing to participate in these sorts of markets.


Originally posted in the Dartmouth College Computer Science Technical Report Series, number TR2015-781.