A novel recommendation framework for micro-blogging based on information diffusion

Aaron R. Sun, Jiesi Cheng, Daniel D. Zeng

Research output: Contribution to conferencePaper

15 Scopus citations

Abstract

Micro-blogging is increasingly extending its role from a daily chatting tool into a critical platform for individuals and organizations to seek and share real-time news updates during emergencies. However, extracting useful information from micro-blogging sites poses significant challenges due to the volume of the traffic and the presence of extensive irrelevant personal messages and spams. 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 who play the role of news providers, our approach selects a small subset as recommended emergency news feeds for regular users. We have evaluated our diffusion-based recommendation framework on Twitter during the early outbreak of H1N1 Flu. The preliminary results show that our method leads to more balanced and comprehensive recommendations compared to benchmark approaches.

Original languageEnglish (US)
Pages199-204
Number of pages6
StatePublished - Jan 1 2009
Event19th Workshop on Information Technologies and Systems, WITS 2009 - Phoenix, AZ, United States
Duration: Dec 14 2009Dec 15 2009

Other

Other19th Workshop on Information Technologies and Systems, WITS 2009
CountryUnited States
CityPhoenix, AZ
Period12/14/0912/15/09

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering

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  • Cite this

    Sun, A. R., Cheng, J., & Zeng, D. D. (2009). A novel recommendation framework for micro-blogging based on information diffusion. 199-204. Paper presented at 19th Workshop on Information Technologies and Systems, WITS 2009, Phoenix, AZ, United States.