Trust and Social Collateral

This paper builds a theory of informal contract enforcement in social networks. In our model, relationships between individuals generate social collateral that can be used to control moral hazard when agents interact in a borrowing relationship. We define trust between two agents as the maximum amount that one can borrow from the other, and derive a simple reduced form expression for trust as a function of the social network. We show that trust is higher in more connected and more homogenous societies, and relate our trust measure to commonly used network statistics. Our model predicts that dense networks generate greater welfare when arrangements typically require high trust, and loose networks create more welfare otherwise. Using data on social networks and behavior in dictator games, we document evidence consistent with the quantitative predictions of the model.

A Distributed Method for Trust-Aware Recommendation in Social Networks

This paper contains the details of a distributed trust-aware recommendation system. Trust-base recommenders have received a lot of attention recently. The main aim of trust-based recommendation is to deal the problems in traditional Collaborative Filtering recommenders. These problems include cold start users, vulnerability to attacks, etc.. Our proposed method is a distributed approach and can be easily deployed on social networks or real life networks such as sensor networks or peer to peer networks

The Transformation of Trust in China’s Alternative Food Networks: Disruption, Reconstruction, and Development

Food safety issues in China have received much scholarly attention, yet few studies systematically examined this matter through the lens of trust. More importantly, little is known about the transformation of different types of trust in the dynamic process of food production, provision, and consumption. We consider trust as an evolving interdependent relationship between different actors. We used the Beijing County Fair, a prominent ecological farmers’ market in China, as an example to examine the transformation of trust in China’s alternative food networks. We argue that although there has been a disruption of institutional trust among the general public since 2008 when the melamine-tainted milk scandal broke out, reconstruction of individual trust and development of organizational trust have been observed, along with the emergence and increasing popularity of alternative food networks. Based on more than six months of fieldwork on the emerging ecological agriculture sector in 13 provinces across China as well as monitoring of online discussions and posts, we analyze how various social factors—including but not limited to direct and indirect reciprocity, information, endogenous institutions, and altruism—have simultaneously contributed to the transformation of trust in China’s alternative food networks. The findings not only complement current social theories of trust, but also highlight an important yet understudied phenomenon whereby informal social mechanisms have been partially substituting for formal institutions and gradually have been building trust against the backdrop of the food safety crisis in China

Understanding Co-evolution in Large Multi-relational Social Networks

Understanding dynamics of evolution in large social networks is an important problem. In this paper, we characterize evolution in large multi-relational social networks. The proliferation of online media such as Twitter, Facebook, Orkut and MMORPGs\footnote{Massively Multi-player Online Role Playing Games} have created social networking data at an unprecedented scale. Sony's Everquest 2 is one such example. We used game multi-relational networks to reveal the dynamics of evolution in a multi-relational setting by macroscopic study of the game network. Macroscopic analysis involves fragmenting the network into smaller portions for studying the dynamics within these sub-networks, referred to as `communities'. From an evolutionary perspective of multi-relational network analysis, we have made the following contributions. Specifically, we formulated and analyzed various metrics to capture evolutionary properties of networks. We find that co-evolution rates in trust based `communities' are approximately $60\%$ higher than the trade based `communities'. We also find that the trust and trade connections within the `communities' reduce as their size increases. Finally, we study the interrelation between the dynamics of trade and trust within `communities' and find interesting results about the precursor relationship between the trade and the trust dynamics within the `communities'

Growth aspirations and social capital: Young firms in a post-conflict environnment

We explore the social determinants of growth aspirations of young firms’ owners and managers in a post-conflict economy. We focus on social capital, which we treat as a multi-dimensional phenomenon, studying not only the effect of owners’ and managers’ personal networks on growth aspirations, but also other facets that facilitate cooperation such as trust in institutions and generalised trust in people. We posit that that the generalised trust amplifies the beneficial effects of personal business networks, explaining how this conclusion diverges from earlier literature. We argue that in a post-conflict country, preservation of ethnic diversity is indicative of tolerance and low communication barriers and social capital appropriable for entrepreneurship. Our empirical counterpart and hypotheses testing rely on survey of young businesses in Bosnia and Herzegovina

How Social Reputation Networks Interact with Competition in Anonymous Online Trading: An Experimental Study

Many Internet markets rely on ‘feedback systems’, essentially social networks of reputation, to facilitate trust and trustworthiness in anonymous transactions. Market competition creates incentives that arguably may enhance or curb the effectiveness of these systems. We investigate how different forms of market competition and social reputation networks interact in a series of laboratory online markets, where sellers face a moral hazard. We find that competition in strangers networks (where market encounters are one-shot) most frequently enhances trust and trustworthiness, and always increases total gains-from-trade. One reason is that information about reputation trumps pricing in the sense that traders usually do not conduct business with someone having a bad reputation not even for a substantial price discount. We also find that a reliable reputation network can largely reduce the advantage of partners networks (where a buyer and a seller can maintain repeated exchange with each other) in promoting trust and trustworthiness if the market is sufficiently competitive. We conclude that, overall, competitive online markets have more effective social reputation networks.reputation systems, e-commerce, internet markets, trust

A trust model for spreading gossip in social networks

We introduce here a multi-type bootstrap percolation model, which we call T-Bootstrap Percolation (T-BP), and apply it to study information propagation in social networks. In this model, a social network is represented by a graph G whose vertices have different labels corresponding to the type of role the person plays in the network (e.g. a student, an educator, etc.). Once an initial set of vertices of G is randomly selected to be carrying a gossip (e.g. to be infected), the gossip propagates to a new vertex provided it is transmitted by a minimum threshold of vertices with different labels. By considering random graphs, which have been shown to closely represent social networks, we study different properties of the T-BP model through numerical simulations, and describe its implications when applied to rumour spread, fake news, and marketing strategies.Comment: 9 pages, 9 figure