Ranking Friends ∗

نویسندگان

  • Yossi Feinberg
  • Willemien Kets
چکیده

We investigate the scope for cooperation within a community engaged in repeated reciprocal interactions. Players seek the help of others and approach them sequentially according to some fixed order, that is, a ranking profile. We study the ranking profiles that correspond to the social structures that are most effective in sustaining cooperation in equilibrium, that is, social structures that support full cooperation in equilibrium under the largest set of parameters. These are the profiles that spread the costs of helping others equally among the members of the community. We show that, generically, these socially optimal ranking profiles correspond to Latin squares – profiles in which each player appears in a given position exactly once in the list of each other player. In addition, we study equilibria with bilateral enforcement in which only the victims punish noncooperating deviators. We show that the Latin squares in which every two players rank each other at the same position characterize the social structures that sustain cooperation for the widest range of parameters in this case. ∗We are grateful to Nageeb Ali, David Kreps, and Brian Rogers for stimulating comments and useful suggestions. †Graduate School of Business, Stanford University. E-mail: [email protected]. ‡Kellogg School of Management, Northwestern University. E-mail: [email protected].

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Alliance Hypothesis for Human Friendship

BACKGROUND Exploration of the cognitive systems underlying human friendship will be advanced by identifying the evolved functions these systems perform. Here we propose that human friendship is caused, in part, by cognitive mechanisms designed to assemble support groups for potential conflicts. We use game theory to identify computations about friends that can increase performance in multi-agen...

متن کامل

Location: How Users Share and Respond to Location-Based Data on Social Networking Sites

In August 2010 Facebook launched Places, a locationbased service that allows users to check into points of interest and share their physical whereabouts with friends. The friends who see these events in their News Feed can then respond to these check-ins by liking or commenting on them. These data consisting of the places people go and how their friends react to them are a rich, novel dataset. ...

متن کامل

Location3: How Users Share and Respond to Location-Based Data on Social

In August 2010 Facebook launched Places, a locationbased service that allows users to check into points of interest and share their physical whereabouts with friends. The friends who see these events in their News Feed can then respond to these check-ins by liking or commenting on them. These data consisting of the places people go and how their friends react to them are a rich, novel dataset. ...

متن کامل

InfoSearch: A Social Search Engine

The staggering growth of online social networking platforms has also propelled information sharing among users in the network. This has helped develop the user-to-content link structure in addition to the already present user-to-user link structure. These two data structures has provided us with a wealth of dataset that can be exploited to develop a social search engine and significantly improv...

متن کامل

Expertise ranking using activity and contextual link measures

Article history: Received 20 April 2010 Received in revised form 24 August 2011 Accepted 25 August 2011 Available online 5 September 2011 The Internet has transformed from a Web of content to a people-centric Web. People actively use social networking platforms to stay in contact with friends and colleagues. The availability of rich Web-based applications allows people to collaborate and intera...

متن کامل

Leveraging Multiactions to Improve Medical Personalized Ranking for Collaborative Filtering

Nowadays, providing high-quality recommendation services to users is an essential component in web applications, including shopping, making friends, and healthcare. This can be regarded either as a problem of estimating users' preference by exploiting explicit feedbacks (numerical ratings), or as a problem of collaborative ranking with implicit feedback (e.g., purchases, views, and clicks). Pre...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012