Group Recommendation System for Facebook

Lecture notes in computer sciencePublished 1 January 2008

Enkh-Amgalan Baatarjav, Santi Phithakkitnukoon, Ram Dantu

DOI10.1007/978-3-540-88875-8_41

Source URL

Citations80

SJR quartileQ2

SJR score0.35

SNIP0.55

TL;DR

This work believes that Facebook SN groups can be identified based on their members' profiles and introduces group recommendation system (GRS) using combination of hierarchical clustering technique and decision tree.

Abstract

Online social networking has become a part of our everyday lives, and one of the popular online social network (SN) sites on the Internet is Facebook, where users communicate with their friends, join to groups, create groups, play games, and make friends around the world. Also, the vast number of groups are created for different causes and beliefs. However, overwhelming number of groups in one category causes difficulties for users to select a right group to join. To solve this problem, we introduce group recommendation system (GRS) using combination of hierarchical clustering technique and decision tree. We believe that Facebook SN groups can be identified based on their members' profiles. Number of experiment results showed that GRS can make 73% accurate recommendation.

Keywords

Computer SciencePhysics and Astronomy

BiometricsClassification and Regression Trees.

23,841 Citations1984Alexander Gordon, Leo Breiman +3 more

Proceedings of the National Academy of SciencesCommunity structure in social and biological networks

15,656 Citations2002Michelle Girvan, M. E. J. Newman

This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.

View PDF

Mining the network value of customers

2,868 Citations2001Pedro Domingos, Matt Richardson

It is proposed to model also the customer's network value: the expected profit from sales to other customers she may influence to buy, the customers those may influence, and so on recursively, taking advantage of the availability of large relevant databases.

Journal of the American Statistical AssociationLatent Space Approaches to Social Network Analysis

1,899 Citations2002Peter D. Hoff, Adrian E. Raftery +1 more

This work develops a class of models where the probability of a relation between actors depends on the positions of individuals in an unobserved “social space,” and proposes Markov chain Monte Carlo procedures for making inference on latent positions and the effects of observed covariates.

Environmental SoftwareCluster analysis for researchers

1,861 Citations1987

Group formation in large social networks

1,820 Citations2006Lars Bäckström, D.P. Huttenlocher +2 more

It is found that the propensity of individuals to join communities, and of communities to grow rapidly, depends in subtle ways on the underlying network structure, and decision-tree techniques are used to identify the most significant structural determinants of these properties.

ComputerSelf-organization and identification of Web communities

1,007 Citations2002Gary William Flake, Sandra Lawrence +2 more

This work shows that the Web self-organizes and its link structure allows efficient identification of communities and is significant because no central authority or process governs the formation and structure of hyperlinks.

Proceedings of the National Academy of SciencesGeographic routing in social networks

857 Citations2005David Liben‐Nowell, Jasmine Novak +3 more

A richer model relating geography and social-network friendship is introduced, in which the probability of befriending a particular person is inversely proportional to the number of closer people.

Internet MathematicsGraph Clustering and Minimum Cut Trees

327 Citations2004Gary William Flake, Robert E. Tarjan +1 more

The clustering algorithms satisfy strong theoretical criteria and perform well in practice, and it is shown that the quality of the produced clusters is bounded by strong minimum cut and expansion criteria.

View PDF

First MondayA social network caught in the Web

268 Citations2003Lada A. Adamic, Orkut Buyukkokten +1 more

Using the rich profile data provided by the users, the analysis of Club Nexus was able to deduce the attributes contributing to the formation of friendships, and to determine how the similarity of users decays as the distance between them in the network increases.

View PDF