Modern black markets have in place numerous institutions to facilitate trade and evade law enforcement. Cash makes transactions untraceable, hierarchy delineates roles and responsibilities, and violence encourages participants to abide by norms. The advent of the Internet razes this system; entirely new institutions are required for black market trades in this environment. The increased anonymity lowers the risk of detection by law enforcement in exchange for an increase in the risk of impropriety between buyer and seller. Seller ratings are used to facilitate trade through lower transaction and information costs.
Illegal Internet activities are conducted on a portion of the Internet referred to as the Dark Net, which is a subset of the Deep Web which is estimated to be thousands of times larger than the Surface Web, the Internet we use every day. The Dark Web is unregulated, untaxed, and hidden from a typical Internet search. It is a self-contained market place that functions under a set of informal institutions. Representative data set mined from The Silk Road, one of the most popular sites on the Deep Web, sheds light on the operation of these black-market transactions. The institution of seller reputations creates a stable trading environment among those least expected to deal honestly: criminals.
Black-market activity on the Deep Web is attractive because of the anonymity it provides. Cryptocurrencies such as Bitcoin (BTC) function like cash; they are relatively untraceable. The TOR network anonymizes web traffic. PGP encryption programs mask data within emails sent between users. These three elements form the technological base upon which Deep Web black markets build, allowing exchange at a much lower cost than previously. Before this technology, sellers and buyers in the black market relied heavily on face-to-face interaction and building a reputation through personal encounters. This shift led to a flourishing peer-to-peer underground marketplace expanding on a global scale.
But, anonymous Internet trading incurs an additional cost. Like buyers and sellers on any peer-to-peer Internet site such as eBay or Amazon, buyers and sellers on the Deep Web rarely, if ever, meet in person. This makes transactions particularly risky because there is no recourse for failure. And unlike goods on Surface Web sites, Deep Web users are buying products much more harmful than ordinary consumer purchases. The unique nature of this marketplace makes the accumulated reputation of users critical to its emergence and sustainability. Similar to Avner Greif’s work on the Maghribi Traders, these Internet traders have asymmetric information. However, unlike the Maghribi Traders, these Internet traders have no legal contract enforceability. Analyzing this reputation component enlightens, more fully, how this market place can exist without any ability to seek recourse ex post and without any prevalence of contract enforceability.
The most important institution of the Deep Web is anonymity. Each buyer and seller is known by a unique username; their true identity is secret. Users of the Deep Web, through forums and blogs, create a wealth of information to keep users updated on the happenings of the market. They use these ‘news outlets’ to keep users informed on frauds, scams, and imposters. Deep Web markets take a cut of each transaction to cover their operation costs and to make a profit. Buyers write and read extensive reviews on sellers and their products. Markets allow ratings from 0 to 5 stars, accompanied by a brief note explaining the rating. More extensive reviews are commonly posted on internal forums and Reddit. These jointly create the seller’s reputation. Some sellers, to differentiate, offer free samples or extra secure shipping techniques to attract positive reviews.
Because of the nature of the goods sold in the Deep Web, on the Silk Road in particular, sellers are anonymous to buyers and buyers are anonymous to sellers. Before a first transaction, they have no personal knowledge of another’s personality and no formal enforcement mechanism if a transaction goes awry. The characteristics of this particular marketplace pose risks to the traders involved. The buyer could refuse to pay the seller after their items have been received, or, if the buyer pays first, the seller could fail to send the purchased items because they received the payment upfront. There is no way to recoup lost BTCs or products once the transaction is finalized. This marketplace exists due to the importance of a bilateral reputation mechanism that instills confidence in the traders and facilitates repeated transactions.
Collecting as much data as possible on the other party is necessary to making a smart and calculated transaction. Initially, buyers and sellers are dependent upon previous users’ feedback for information on the legitimacy of their potential trade. Recognizing this potential risk, traders utilize forums such as Reddit and the Silk Road itself for feedback, bringing attention to fraudulent behavior and informing traders of transaction malfeasance.
The codification of buyer and seller feedback makes up each party’s user profile. A user’s feedback profile in this marketplace is made up of the comments and ratings left on the Silk Road site as well as other feedback forums. This feedback is both comments and a number rating. The collection of this user feedback on other users makes up the reputation of the trader in the marketplace. Due to the anonymity aspects of The Silk Road, buyer information is not formally posted like seller information and feedback is on the site. Unlike Surface Web marketplaces, if a buyer leaves a comment and/or rating, an individual identifier is not attached to their message. The reason for this is to protect buyer anonymity. The only information that we can glean about the buyer in particular is that they did in fact make a purchase; buyers cannot leave feedback on a product they did not buy.
Potential buyers utilize this feedback about sellers. They can read comments about previous buyer’s experiences, whether or not the buyer received the items, and view the seller’s 30-day and 60-day and overall rating score. This score is an average of past reviews and it is out of five possible points. Sellers, however, do not have access to this information about potential buyers. Repeated trade will reveal buyer reputation, but the first is made with little information. The promise of future trade can incentivize honest behavior from the beginning; sellers can cease trade with dishonest buyers.
Discovery of a dishonest buyer can have positive externalities for other sellers. But, sellers’ outlets for relaying the information that they have learned from buyers are limited. Because buyers do not have publically available profiles, the seller must seek alternative forms of feedback. They can leave feedback on the internal Silk Road forums or various forums on the Surface Web, but cannot add to a collected reputation buyer profile because they do not exist.
Gambetta, identifies that criminals need both a costly signal of the trader’s credentials and a costless arbitrary group signal in order for this type of market place to run smoothly underground. The components necessary for a successful reputation signal must be easily observable and that they also must be costly for cheaters to signal a stellar reputation and fairly inexpensive for honest users to signal that they are authentic.
Applying these characteristics to the Silk Road marketplace, the seller feedback mechanisms of readily observable ratings, comments, and thus reputation fit these criteria and send a signal that the seller is honest or dishonest. It would be difficult for a repeatedly dishonest seller to trick its buyers to leave positive reviews and ratings even though the products and services were a sham. On the other hand, if an honest seller provides their customers with quality products in a timely manner, it will be relatively easy to receive truthful positive reviews about the seller’s quality performance. This dovetails very nicely with what we know about the Silk Road community from studying Silk Road forums: the community is very active at giving feedback. These criteria, easily observable signaling and costly signaling for cheaters, do not necessarily apply to the buyers in this marketplace. This failure of buyer feedback to meet the strong signal criteria proposes that buyer signals could contain a great deal of noise and potential for misread signals. For the purposes of this paper, we will analyze the impact of seller’s reputation as a signal.
However imperfect these feedback mechanisms may be, they provide users information on reputation. Reputation is crucial in this market because it acts as a signal to other users that they are honest and credible individuals. This signal works to differentiate between honest and dishonest users to ensure that honest users are not driven out of the marketplace by dishonest users that are not properly identified. The traders’ identities work to reduce social distance in the marketplace. Deep Web traders do not have an identity in the traditional sense; however, they foster an identity through their online reputation. People cheat because they have higher discount rates than their cooperators. Their gains from future exchange are more heavily discounted, thus they invest less because it is more costly for them.
These feedback mechanisms have created an informal institutional framework within which traders exchange goods with confidence. This marketplace demonstrates the shifting institutional structure of black markets in response to new technologies and threats. Sellers are able to charge premium prices due to their higher relative reputations, this incentivizes them to work to increase their reputation. This particular incentive structure further solidifies the theory that reputation mechanisms are effective. Good reputations allow sellers to make more money and sellers are incentivized to provide quality service to their customers so that they increase their reputation and thus, make higher profits.
The entire paper, Reputation in the Internet black market: an empirical and theoretical analysis of the Deep Web, can be found at https://www.gwern.net/docs/sr/2015-hardy.pdf