An epidemic model for news spreading on twitter

Saeed Abdullah, Xindong Wu

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

35 Scopus citations

Abstract

In this paper, we describe a novel approach to understand and explain news spreading dynamics on Twitter by using well-known epidemic models. Our underlying hypothesis is that the information diffusion on Twitter is analogous to the spread of a disease. As mathematical epidemiology has been extensively studied, being able to express news spreading as an epidemic model enables us to use a wide range of tools and procedures which have been proven to be both analytically rich and operationally useful. To further emphasize this point, we also show how we can readily use one of such tools - a procedure for detection of influenza epidemics, to detect change of trend dynamics on Twitter.

Original languageEnglish (US)
Title of host publicationProceedings - 2011 23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011
Pages163-169
Number of pages7
DOIs
StatePublished - Dec 1 2011
Event23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011 - Boca Raton, FL, United States
Duration: Nov 7 2011Nov 9 2011

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (Print)1082-3409

Other

Other23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011
CountryUnited States
CityBoca Raton, FL
Period11/7/1111/9/11

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Computer Science Applications

Cite this

Abdullah, S., & Wu, X. (2011). An epidemic model for news spreading on twitter. In Proceedings - 2011 23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011 (pp. 163-169). [6103322] (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI). https://doi.org/10.1109/ICTAI.2011.33