Reputation Tracking Research Articles

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.

Toward a Reputation State: The Social Credit System Project of China

The ongoing “reputation revolution,” as it refers to the widespread adoption of reputation tracking and analytics, is now seeing its frontier shifting from the “reputation society” to the “reputation state”: Government authorities, following the steps of private sector players, now increasingly seek to use reputation mechanisms and technologies in the spheres of law and governance. In 2014, China’s national government unveiled a massive policy plan for building a “social credit system” in China (hereinafter the “SCSP,” which stands for the “social credit system project”). In designing the SCSP, the Chinese government envisioned that reputation mechanisms such as blacklisting, rating, and scoring be used to tackle many of the country’s by far intractable governance and regulatory problems in its social and economic realms, ranging from fraudulent behaviors in the marketplace, to difficulties in enforcing court judgments, to corruption in the government, and to professional malpractices and even plagiarism in scholarship. Although Western governments have also explored using reputation technologies and mechanisms in governance and social control contexts, China’s SCSP, as a comprehensive, singularly framed, and actively implemented policy project, knows no equivalent elsewhere in the world, and thus offers a unique case for studying a rise of the reputation state as a broader trend. This Article provides a systematic descriptive and analytical study on the SCSP. It draws on the general theoretical discussions on the reputation state to identify four key strategies, categorized in this Article as “regulation,” “searchlight,” “incorporation,” and “institutionalization,” which government actors may plausibly employ as they seek to use reputation for law and public administration. While Western experiences already illustrate ways in which these strategies may actually work in practical contexts, China’s SCSP takes the reputation state into the uncharted territory as it explores novel possibilities. Upon examining the major policy initiatives included, this Article finds that the SCSP overall represents the effort of China’s developmental state to tackle its persistent governance problems with new tools. While it has both raised high hopes and stoke grave fears, the SCSP, as this Article explains, has been fundamentally shaped and also limited by many of the institutional and market forces that animate it in the first place. Nonetheless, if future institutional arrangements and technological progress could align to overcome the present implementation challenges, the reputation state effected through the SCSP does have the potential to change law and government as we know them in China and beyond. Specifically, this Article offers initial thoughts on the SCSP’s plausible implications in three areas that are important but inadequately explored, relating in broad terms to government expansion and efficiency, optimal approach to enforcement, and intragovernmental agency control.

The Best Answers? Think Twice: Identifying Commercial Campagins in the CQA Forums

In an emerging trend, more and more Internet users search for information from Community Question and Answer (CQA) websites, as interactive communication in such websites provides users with a rare feeling of trust. More often than not, end users look for instant help when they browse the CQA websites for the best answers. Hence, it is imperative that they should be warned of any potential commercial campaigns hidden behind the answers. Existing research focuses more on the quality of answers and does not meet the above need. Textual similarities between questions and answers are widely used in previous research. However, this feature will no longer be effective when facing commercial paid posters. More context information, such as writing templates and a user’s reputation track, needs to be combined together to form a new model to detect the potential campaign answers. In this paper, we develop a system that automatically analyzes the hidden patterns of commercial spam and raises alarms instantaneously to end users whenever a potential commercial campaign is detected. Our detection method integrates semantic analysis and posters’ track records and utilizes the special features of CQA websites largely different from those in other types of forums such as microblogs or news reports. Our system is adaptive and accommodates new evidence uncovered by the detection algorithms over time. Validated with real-world trace data from a popular Chinese CQA website over a period of three months, our system shows great potential towards adaptive detection of CQA spams.

From open-source software to Wikipedia: ‘Backgrounding’ trust by collective monitoring and reputation tracking

Open-content communities that focus on co-creation without requirements for entry have to face the issue of institutional trust in contributors. This research investigates the various ways in which these communities manage this issue. It is shown that communities of open-source software--continue to--rely mainly on hierarchy (reserving write-access for higher echelons), which substitutes (the need for) trust. Encyclopedic communities, though, largely avoid this solution. In the particular case of Wikipedia, which is confronted with persistent vandalism, another arrangement has been pioneered instead. Trust (i.e. full write-access) is `backgrounded' by means of a permanent mobilization of Wikipedians to monitor incoming edits. Computational approaches have been developed for the purpose, yielding both sophisticated monitoring tools that are used by human patrollers, and bots that operate autonomously. Measures of reputation are also under investigation within Wikipedia; their incorporation in monitoring efforts, as an indicator of the trustworthiness of editors, is envisaged. These collective monitoring efforts are interpreted as focusing on avoiding possible damage being inflicted on Wikipedian spaces, thereby being allowed to keep the discretionary powers of editing intact for all users. Further, the essential differences between backgrounding and substituting trust are elaborated. Finally it is argued that the Wikipedian monitoring of new edits, especially by its heavy reliance on computational tools, raises a number of moral questions that need to be answered urgently.

Secure Electronic Marketplaces Based on the Multi Agent System Avalanche

The future of electronic commerce will be shaped by open, heterogeneous and complex structures, consisting of many independent marketplaces. For conducting transactions, businesses have to be present at many of these marketplaces all over the Internet. But software agents, who interact and negotiate on behalf of their human (or organizational) principals, can act as representatives here. The multi-agent system AVALANCHE is a prototype for an agent based secure electronic commerce marketplace environment. The processes are coordinated by the use of autonomous, self-interested software agents, representing consumers and small businesses. The marketplace itself offers a directory service, but never actively influences the agents' activities. The agents communicate by passing messages bilaterally using an iterated contract-net protocol. Businesses who try to sell and buy goods first configure a (mobile) agent in their web browser or PDA and send it to any electronic marketplace to negotiate autonomously. In case that the agent's demand is not met, it can move to other marketplaces in search for a better offer or demand situation. If the agent finds a promising situation, it automatically starts a negotiation process, which will eventually lead to a market transaction. The software agents are able to adapt their changing environment to their negotiation strategies through the use of evolutionary algorithms. Since the agents are conducting their businesses over an open and insecure network, some technical security mechanisms have been implemented. The code-obfuscated agents digitally sign their offers and encrypt their messages. But the self-interested behavior of the agents demands additional mechanisms, which exceed technical security, to ensure co-operational behavior. Currently a reputation tracking mechanism is implemented that evaluates a partner's former transaction behavior and thus influences both partner selection and negotiation strategy for future transactions. In case that an agent plans to conduct a transaction with an unknown agent, it may be able to source the reputation information from either the marketplace or other known agents, depending on the system of information collection, storage, and distribution. This rating of reputation is then updated during the settlement phase of any transaction.

Indirect reciprocity and the evolution of “moral signals”

Signals regarding the behavior of others are an essential element of human moral systems and there are important evolutionary connections between language and large-scale cooperation. In particular, social communication may be required for the reputation tracking needed to stabilize indirect reciprocity. Additionally, scholars have suggested that the benefits of indirect reciprocity may have been important for the evolution of language and that social signals may have coevolved with large-scale cooperation. This paper investigates the possibility of such a coevolution. Using the tools of evolutionary game theory, we present a model that incorporates primitive “moral signaling” into a simple setting of indirect reciprocity. This model reveals some potential difficulties for the evolution of “moral signals.” We find that it is possible for “moral signals” to evolve alongside indirect reciprocity, but without some external pressure aiding the evolution of a signaling system, such a coevolution is unlikely.

COBRA – mining web for COrporate Brand and Reputation Analysis

Corporations are extremely sensitive to issues such as brand stewardship and product reputation. Traditional brand image and reputation tracking is limited to news wires and contact centre analysis. However, with the emergence of web, Consumer Generated Media (CGM), such as blogs, news forums, message boards, and web pages/sites, is rapidly becoming the “voice of the people”. Effectively leveraging such readily available and massive amount of CGM content for brand and reputation insights can be extremely valuable to corporations. Yet the existing solutions in this space are commonly limited to keyword search based technologies that often result in excessive amount of information for users to digest manually. Some text mining based technologies exist for mining the web. However, they often target very narrow problems such as web page classification instead of looking at the overall stack of technologies required for web mining. This paper describes a holistically integrated brand and reputation analysis solution that mines CGM contents for insights, called COBRA (COrporate Brand and Reputation Analysis). COBRA contains a flexible ETL (Extract, Transform, and Load) engine that processes diverse sets of structured and unstructured information, a suite of analytical capabilities that mines CGM content to extract semantic entities and insights out of the data, and an alerting mechanism that utilizes a technique called “orthogonal filtering” to accurately generate brand and reputation alerts by filtering through orthogonal dimensions of information. We use a set of real-world case studies to demonstrate the effectiveness of our overall approach. We show that by applying such analytics techniques, we significantly improved the accuracy of alert identification by 10-200 times when compared to the popular keyword-search based techniques in today's alerting systems.

Trade-offs between reliability and overheads in peer-to-peer reputation tracking

The success of incentive techniques to motivate freeriders to contribute resources in file-sharing Gnutella-like peer-to-peer networks depends on the availability of peer behavior tracking in terms of resource consumption and contribution. Though many reputation systems have been proposed toward the goal of behavior tracking, the overheads incurred in such tracking have received little attention. Consideration of overheads is an important factor in judging the merits of a practical reputation tracking scheme in order to maintain the scalability of the underlying peer-to-peer network. This paper proposes two methods of reputation tracking: strong and weak reputations. These methods differ in the trade-offs between reliability of reputation tracking and the overheads incurred. We formally specify and verify strong reputations and note that while the scheme yields highly reliable reputation tracking, the reliability and overhead trade-offs in weak reputations present a more viable alternative for large peer-to-peer networks.

Emerging roles for third parties in cyberspace

In `real' space, third parties have always been useful to facilitate transactions. With cyberspace opening up, it is to be expected that intermediation will also develop in a virtual fashion. The article focuses upon new cyberroles for third parties that seem to announce themselves clearly. First, virtualization of the market place has paved the way for `cybermediaries', who broker between supply and demand of material and informational goods. Secondly, cybercommunication has created new uncertainties concerning informational security and privacy. Also, as in real space, transacting supposes some decency with one's partners. These needs are being addressed by Trusted Third Parties, anonymizers, escrow arrangements, facilitators and external auditing. Virtual reputation tracking mechanisms are being developed as well. Finally, in order to resolve disputes, mediators and arbitrators have started offering their services online. In the closing section these emerging cyberroles are assessed critically. It is argued in particular, that both cybermediaries and cyberjustice pose serious threats to privacy. Moreover, online dispute resolution, as it is practised now, neglects its duties of public accounting.