The Study of Cryptocurrency Marketplaces: User similarities in peer-to-peer Cryptocurrency markets; Understanding users of peer-to-peer exchanges and the applications and their impact on digital marketplaces.

The general topic that was addressed centered around analyzing who participated in peer-to-peer cryptocurrency trading networks and why an individual might want to trade on this type of network instead of a more established currency exchange. I worked to create web scrapes of different users of the website HODLHODL.com which was the primary focus of the Capstone research project. The focus of the STS research paper was on how peer-to-peer networks form and the different actors who make up the network.
The technical research was vital in acquiring information about the users of HODLHODL.com for the STS Research paper. The two projects were tied together in studying the features of the website and how user information was stored and what the typical user entered regarding their information. It was found that most users preferred to remain as anonymous as possible, and the creators of this site catered to this by requiring very little information to make trades on the site.
In this project I was successful in creating a web scrape of the different profiles that existed on HODLHODL.com. This project helped me learn more about seeking help from other experts within my company who had experience designing similar web scrapers. I was able to be guided by viewing their old projects and they also assisted me in designing a web scraper for my specific project. Further research is possible since there are many peer-to-peer cryptocurrency exchanges, and in the future designing a web scrape which can work for dynamic websites with yield more information but are slightly more difficult to design. An ability to further the information gathered about the users would be very beneficial but because the sites are marketed because of the anonymity offered it was very difficult to conclude very much about the users. By collecting more information from different websites researchers might be able to detect patterns to identify users which would be helpful in determining more about who are the users of these anonymous trading platforms.

School of Engineering and Applied Science
Bachelor of Science in Computer Science
Technical Advisor: Rosanne Vrugtman
STS Advisor: Sean Ferguson