Name
Abstract | ||
|---|---|---|
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 influence the resultant ranking. We show the benefits of considering trust relationships, and define the form of the algorithm better apt to common situations. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-34624-8_46 | ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems |
Keywords | DocType | Volume |
resultant ranking,algorithm influence,internet era,online community,general ranking method,trust relationship,real online community,econophysics forum,quality content,information overload | Conference | abs/1208.4042 |
ISSN | Citations | PageRank |
Lecture Notes in Computer Science 7661, 405-414 (2012) | 7 | 0.51 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao Liao | 1 | 51 | 5.37 |
| Giulio Cimini | 2 | 126 | 13.77 |
| Matúš Medo | 3 | 7 | 0.51 |