We analyze an agent-based model to estimate how the costs and benefits of users in an online social network (OSN) impact the robustness of the OSN. Benefits are measured in terms of relative reputation that users receives from their followers. They can be increased by direct and indirect reciprocity in following each other, which leads to a core-periphery structure of the OSN. Costs relate to the effort to login, to maintain the profile, etc. and are assumed as constant for all users. The robustness of the OSN depends on the entry and exit of users over time. Intuitively, one would expect that higher costs lead to more users leaving and hence to a less robust OSN. We demonstrate that an optimal cost level exists, which maximizes both the performance of the OSN, measured by means of the long-term average benefit of its users, and the robustness of the OSN, measured by means of the life-time of the core of the OSN. Our mathematical and computational analyses unfold how changes in the cost level impact reciprocity and subsequently the core-periphery structure of the OSN, to explain the optimal cost level.
The peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases digital reputation, revealing that P2P networks display exceedingly high levels of reciprocity. In fact, these are much higher than those compatible with a null assumption that preserves the empirically observed level of agreement between all pairs of nodes, and rather close to the highest levels structurally compatib…
Indirect reciprocity in which players cooperate with unacquainted other players having good reputations is a mechanism for cooperation in relatively large populations subjected to social dilemma situations. When the population has group structure, as is often found in social networks, players in experiments are considered to show behavior that deviates from existing theoretical models of indirect reciprocity. First, players often show ingroup favoritism (i.e., cooperation only within the group) rather than full cooperation (i.e., cooperation within and across groups), even though the latter is…
Indirect reciprocity is a mechanism for cooperation in social dilemma situations, in which an individual is motivated to help another to acquire a good reputation and receive help from others afterwards. Ingroup favoritism is another aspect of human cooperation, whereby individuals help members in their own group more often than those in other groups. Ingroup favoritism is a puzzle for the theory of cooperation because it is not easily evolutionarily stable. In the context of indirect reciprocity, ingroup favoritism has been shown to be a consequence of employing a double standard when assigni…
Cooperation can be supported by indirect reciprocity via reputation.Thanks to gossip, reputations are built and circulated and humans can identify defectors and ostracise them. However, the evolutionary stability of gossip is allegedly undermined by the fact that it is more error-prone that direct observation, whereas ostracism could be ineffective if the partner selection mechanism is not robust. The aim of this work is to investigate the conditions under which the combination of gossip and ostracism might support cooperation in groups of different sizes. We are also interested in exploring t…
In dyadic models of indirect reciprocity, the receivers' history of giving has a significant impact on the donor's decision. When the interaction involves more than two agents things become more complicated, and in large groups cooperation can hardly emerge. In this work we use a Public Goods Game to investigate whether publicly available reputation scores may support the evolution of cooperation and whether this is affected by the kind of network structure adopted. Moreover, if agents interact on a bipartite graph with partner selection cooperation can thrive in large groups and in a small am…
Despite recent advances in reputation technologies, it is not clear how reputation systems can affect human cooperation in social networks. Although it is known that two of the major mechanisms in the evolution of cooperation are spatial selection and reputation-based reciprocity, theoretical study of the interplay between both mechanisms remains almost uncharted. Here, we present a new individual-based model for the evolution of reciprocal cooperation between reputation and networks. We comparatively analyze four of the leading moral assessment rules---shunning, image scoring, stern judging, …
In the Internet era the information overload and the challenge to detect quality content has raised the issue of how to rank both resources and users in online communities. In this paper we develop a general ranking method that can simultaneously evaluate users' reputation and objects' quality in an iterative procedure, and that exploits the trust relationships and social acquaintances of users as an additional source of information. We test our method on two real online communities, the EconoPhysics forum and the Last.fm music catalogue, and determine how different variants of the algorithm i…
Scientific coauthorship, generated by collaborations and competitions among researchers, reflects effective organizations of human resources. Researchers, their expected benefits through collaborations, and their cooperative costs constitute the elements of a game. Hence we propose a cooperative game model to explore the evolution mechanisms of scientific coauthorship networks. The model generates geometric hypergraphs, where the costs are modelled by space distances, and the benefits are expressed by node reputations, i. e. geometric zones that depend on node position in space and time. Model…
Evolutionary game theory predicts that cooperation in social dilemma games is promoted when agents are connected as a network. However, when networks are fixed over time, humans do not necessarily show enhanced mutual cooperation. Here we show that reinforcement learning (specifically, the so-called Bush-Mosteller model) approximately explains the experimentally observed network reciprocity and the lack thereof in a parameter region spanned by the benefit-to-cost ratio and the node's degree. Thus, we significantly extend previously obtained numerical results.
Individual and collective gains from cooperation and reciprocity in a dynamic-network Prisoner's Dilemma driven by extraversion, openness, and agreeableness
Departamento de Informática e Ingeniería de Sistemas, Universidad de Zaragoza（萨拉戈萨大学计算机与系统工程系）；Instituto de Investigación en Ingeniería de Aragón (I3A), Universidad de Zaragoza（阿拉贡工程研究所 (I3A)，萨拉戈萨大学）
Reciprocity is firmly established as an important mechanism that promotes cooperation. An efficient information exchange is likewise important, especially on structured populations, where interactions between players are limited. Motivated by these two facts, we explore the role of facilitators in social dilemmas on networks. Facilitators are here mirrors to their neighbors -- they cooperate with cooperators and defect with defectors -- but they do not participate in the exchange of strategies. As such, in addition to introducing direct reciprocity, they also obstruct information exchange. In …
Social networks are pivotal for learning. Yet, we still lack a full understanding of the mechanisms connecting networks with learning outcomes. Here, we present the results of a large scale study (946 elementary school children from 45 different classrooms) designed to understand the social strategies used by elementary school children. We mapped the social networks of students using both, a non-anonymous version of a prisoner's dilemma and a survey of nominated friendships, and compared the strategies played by students with their GPAs. We found that higher GPA students invest more strategica…
Crowdsourcing websites (e.g. Yahoo! Answers, Amazon Mechanical Turk, and etc.) emerged in recent years that allow requesters from all around the world to post tasks and seek help from an equally global pool of workers. However, intrinsic incentive problems reside in crowdsourcing applications as workers and requester are selfish and aim to strategically maximize their own benefit. In this paper, we propose to provide incentives for workers to exert effort using a novel game-theoretic model based on repeated games. As there is always a gap in the social welfare between the non-cooperative equil…
Kleinberg proposed a family of small-world networks to explain the navigability of large-scale real-world social networks. However, the underlying mechanism that drives real networks to be navigable is not yet well understood. In this paper, we present a game theoretic model for the formation of navigable small world networks. We model the network formation as a Distance-Reciprocity Balanced (DRB) game in which people seek for both high reciprocity and long-distance relationships. We show that the game has only two Nash equilibria: One is the navigable small-world network, and the other is the…
How does one develop a new online community that is highly engaging to each user and promotes social interaction? A number of websites offer friend-finding features that help users bootstrap social networks on the website by copying links from an established network like Facebook or Twitter. This paper quantifies the extent to which such social bootstrapping is effective in enhancing a social experience of the website. First, we develop a stylised analytical model that suggests that copying tends to produce a giant connected component (i.e., a connected community) quickly and preserves propert…
Online communities adopt various reputation schemes to measure content quality. This study analyzes the effect of a new reputation scheme that exposes one's offline social status, such as an education degree, within an online community. We study two Reddit communities that adopted this scheme, whereby posts include tags identifying education status referred to as flairs, and we examine how the "transferred" social status affects the interactions among the users. We computed propensity scores to test whether flairs give ad-hoc authority to the adopters while minimizing the effects of confoundin…
Empirical data shows that in the absence of incentives, a peer participating in a Peer-to-Peer (P2P) network wishes to free-riding. Most solutions for providing incentives in P2P networks are based on direct reciprocity, which are not appropriate for most P2P multimedia sharing networks due to the unique features exhibited by such networks: large populations of anonymous agents interacting infrequently, asymmetric interests of peers, network errors, and multiple concurrent transactions. In this paper, we design and rigorously analyze a new family of incentive protocols that utilizes indirect r…
Online Social Networking is a fascinating phenomena, attracting more than one billion people. It supports basic human needs such as communication, socializing with others and reputation building. Thus, an in-depth understanding of user behavior in Online Social Networks (OSNs) can provide major insights into human behavior, and impacts design choices of social platforms and applications. However, researchers have only limited access to behavioral data. As a consequence of this limitation, user behavior in OSNs as well as its development in recent years are still not deeply understood. In this …
