On the efficiency of social recommender networks

Felix Ming Fai Wong, Zhenming Liu, Mung Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


We study a fundamental question that arises in social recommender systems: whether it is possible to simultaneously maximize (a) an individual's benefit from using a social network and (b) the efficiency of the network in disseminating information. To tackle this question, our study consists of three components. First, we introduce a stylized stochastic model for recommendation diffusion. Such a model allows us to highlight the connection between user experience at the individual level, and network efficiency at the macroscopic level. We also propose a set of metrics for quantifying both user experience and network efficiency. Second, based on these metrics, we extensively study the tradeoff between the two factors in a Yelp dataset, concluding that Yelp's social network is surprisingly efficient, though not optimal. Finally, we design a friend recommendation and news feed curation algorithm that can simultaneously address individuals' need to connect to high quality friends, and service providers' need to maximize network efficiency in information propagation.

Original languageEnglish (US)
Title of host publication2015 IEEE Conference on Computer Communications, IEEE INFOCOM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781479983810
StatePublished - Aug 21 2015
Event34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015 - Hong Kong, Hong Kong
Duration: Apr 26 2015May 1 2015

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Other34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015
Country/TerritoryHong Kong
CityHong Kong

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


Dive into the research topics of 'On the efficiency of social recommender networks'. Together they form a unique fingerprint.

Cite this