Quick Search:

uzh logo
Browse by:


Zurich Open Repository and Archive

Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-60493

Chen, Jiesi; Sun, Runpu; Hu, Daning; Zeng, Dajun (2011). An information diffusion-based recommendation framework for micro-blogging. Journal of the Association for Information Systems, 12(7):463-486.

[img]Published Version
PDF - Registered users only


Micro-blogging is increasingly evolving from a daily chatting tool into a critical platform for individuals and organizations to seek and share real-time news updates during emergencies. However, seeking and extracting useful information from micro-blogging sites poses significant challenges due to the volume of the traffic and the presence of a large body of irrelevant personal messages and spam. In this paper, we propose a novel recommendation framework to overcome this problem. By analyzing information diffusion patterns among a large set of micro-blogs that play the role of emergency news providers, our approach selects a small subset as recommended emergency news feeds for regular users. We evaluate our diffusion-based recommendation framework on Twitter during the early outbreak of H1N1 Flu. The evaluation results show that our method results in more balanced and comprehensive recommendations compared to benchmark approaches.



3 downloads since deposited on 21 Mar 2012
0 downloads since 12 months

Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Deposited On:21 Mar 2012 10:26
Last Modified:29 Dec 2013 02:25
Publisher:Association for Information Systems
Official URL:http://aisel.aisnet.org/jais/vol12/iss7/2/
Other Identification Number:merlin-id:6373

Users (please log in): suggest update or correction for this item

Repository Staff Only: item control page