By Topic

Organization of social network messages to improve understanding of an evolving crisis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Platt, A. ; Network Syst. Lab., Illinois Inst. of Technol., Chicago, IL, USA ; Hood, C. ; Citrin, L.

In this work, we present a system that is implemented on top of a stream of social network messages to facilitate learning about an emerging crisis. This method automatically detects sub-topics of the topic (crisis), and populates the sub-topics with the relevant retrieved messages. In future work, we intend to reduce the repetitiveness of the generated sub-topics while maintaining high precision in our classification, and implementing other unsupervised learning versions of our method and comparing them to the KNN version.

Published in:

Intelligence and Security Informatics (ISI), 2011 IEEE International Conference on

Date of Conference:

10-12 July 2011