Arbitrary Inequality in Reputation Systems

The effects of reputation on inequality in network cooperation games

In the last several decades, ample evidence from across evolutionary biology, behavioural economics and econophysics has solidified our knowledge that reputation can promote cooperation across different contexts and environments. Higher levels of cooperation entail higher final payoffs on average, but how are these payoffs distributed among individuals? This study investigates how public and objective reputational information affects payoff inequality in repeated social dilemma interactions in large groups. I consider two aspects of inequality: excessive dispersion of final payoffs and diminished correspondence between final payoff and cooperative behaviour. I use a simple heuristics-based agent model to demonstrate that reputational information does not always increase the dispersion of final payoffs in strategically updated networks, and actually decreases it in randomly rewired networks. More importantly, reputational information almost always improves the correspondence between final payoffs and cooperative behaviour. I analyse empirical data from nine experiments of the repeated Trust, Helping, Prisoner's Dilemma and Public Good games in networks of ten or more individuals to provide partial support for the predictions. Our research suggests that reputational information not only improves cooperation but may also reduce inequality. This article is part of the theme issue 'The language of cooperation: reputation and honest signalling'.

When does reputation lie? Dynamic feedbacks between costly signals, social capital and social prominence

Performing a dramatic act of religious devotion, creating an art exhibit, or releasing a new product are all examples of public acts that signal quality and contribute to building a reputation. Signalling theory predicts that these public displays can reliably reveal quality. However, data from ethnographic work in South India suggests that more prominent individuals gain more from reputation-building religious acts than more marginalized individuals. To understand this phenomenon, we extend signalling theory to include variation in people's social prominence or social capital, first with an analytical model and then with an agent-based model. We consider two ways in which social prominence/capital may alter signalling: (i) it impacts observers' priors, and (ii) it alters the signallers' pay-offs. These two mechanisms can result in both a 'reputational shield,' where low quality individuals are able to 'pass' as high quality thanks to their greater social prominence/capital, and a 'reputational poverty trap,' where high quality individuals are unable to improve their standing owing to a lack of social prominence/capital. These findings bridge the signalling theory tradition prominent in behavioural ecology, anthropology and economics with the work on status hierarchies in sociology, and shed light on the complex ways in which individuals make inferences about others. This article is part of the theme issue 'The language of cooperation: reputation and honest signalling'.

Reviewing Stranger on the Internet: The Role of Identifiability through “Reputation” in Online Decision Making

The stranger on the Internet effect has been studied in relation to self-disclosure. Nonetheless, quantitative evidence about how people mentally represent and perceive strangers online is still missing. Given the dynamic development of web technologies, quantifying how much strangers can be considered suitable for pro-social acts such as self-disclosure appears fundamental for a whole series of phenomena ranging from privacy protection to fake news spreading. Using a modified and online version of the Ultimatum Game (UG), we quantified the mental representation of the stranger on the Internet effect and tested if people modify their behaviors according to the interactors’ identifiability (i.e., reputation). A total of 444 adolescents took part in a 2 × 2 design experiment where reputation was set active or not for the two traditional UG tasks. We discovered that, when matched with strangers, people donate the same amount of money as if the other has a good reputation. Moreover, reputation significantly affected the donation size, the acceptance rate and the feedback decision making as well.

Reputation transferability across contexts: Maintaining cooperation among anonymous cryptomarket actors when moving between markets

BACKGROUND

Buyers and sellers of illegal drugs in cryptomarkets have been found to overcome trust issues created by anonymity and the lack of legal protection with the help of reputation systems. Cryptomarkets rarely operate for longer than a year before closing or getting shut down due to external shocks, such as law enforcement operations. This results in large flows of users migrating between market platforms. An important question in order to better understand why cryptomarkets recover quickly after external shocks is: to what extent can reputation be carried over between different markets? This problem is non-trivial given the anonymity of cryptomarket users and the fact that reputation is tied to a user's online identity. Here we analyze conditions under which sellers choose to migrate with the same identity and whether reputation history from previous cryptomarkets yields benefits in new contexts.

METHODS

We analyze sellers' migration in three cryptomarkets (Abraxas, Agora and AlphaBay) and follow their reputation history by linking user accounts between marketplaces using the Grams database. We use longitudinal multi-level regression models to compare market success of migrant and non-migrant sellers. In total, the data contains more than 7,500 seller account and 2.5 million buyers' reputational feedback messages over a period of 3 years.

FINDINGS

It is predominantly the successful sellers with a large number of sales and high reputation who choose to migrate and maintain their identity using cryptographic methods after market closures. We find that reputation history from previous markets creates a competitive advantage to migrant sellers compared to market entrants.

CONCLUSION

Reputation transferability embeds cryptomarket users beyond a single market platform, which incentivizes cooperative behavior. The results also suggest that reputation transferability might contribute to a quick recovery of online drug trade after shutdowns and accumulation of market share in the hands of a small fraction of successful sellers.

The effect of competition on discrimination in online markets-Anonymity and selection

Empirical studies show that discrimination by identity found in offline markets also prevails online. This paper reveal that in a competitive market, buyers that intend to discriminate exist but they are prevented from influencing the market outcome. To this end, we construct a field experiment on eBay, where half of the sellers disclose their names in their usernames while the other half do not. eBay, however, automatically discloses the seller’s names to the buyer after the auction. In the anonymous auctions, winning bidders thus learn the identity of the seller after the auction ends, and here we find buyers to discriminate against sellers with foreign-sounding names by leaving them feedback less often. However, there is no such discrimination in feedback provision when the seller name was known to the buyer before the auction. When bidders know the names of the sellers, the bidders with animus towards individuals with specific names can select out of auctions from these sellers, leaving winners that do not discriminate. One would expect that the auctions of for example sellers with foreign-sounding names would receive fewer bidders and thus lower auction prices. However, we observe no such differences: there are no statistically significant differences in the number of bids or auction prices received by sellers with foreign or domestic sounding names.

The emergence of inequality in social groups: Network structure and institutions affect the distribution of earnings in cooperation games

From small communities to entire nations and society at large, inequality in wealth, social status, and power is one of the most pervasive and tenacious features of the social world. What causes inequality to emerge and persist? In this study, we investigate how the structure and rules of our interactions can increase inequality in social groups. Specifically, we look into the effects of four structural conditions—network structure, network fluidity, reputation tracking, and punishment institutions—on the distribution of earnings in network cooperation games. We analyze 33 experiments comprising 96 experimental conditions altogether. We find that there is more inequality in clustered networks compared to random networks, in fixed networks compared to randomly rewired and strategically updated networks, and in groups with punishment institutions compared to groups without. Secondary analyses suggest that the reasons inequality emerges under these conditions may have to do with the fact that fixed networks allow exploitation of the poor by the wealthy and clustered networks foster segregation between the poor and the wealthy, while the burden of costly punishment falls onto the poor, leaving them poorer. Surprisingly, we do not find evidence that inequality is affected by reputation in a systematic way but this could be because reputation needs to play out in a particular network environment in order to have an effect. Overall, our findings suggest possible strategies and interventions to decrease inequality and mitigate its negative impact, particularly in the context of mid- and large-sized organizations and online communities.