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Q-analysis based clustering of online news

Sousa-Rodrigues, David (2014). Q-analysis based clustering of online news. Discontinuity, Nonlinearity, and Complexity, 3(3) pp. 227–236.

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DOI (Digital Object Identifier) Link: https://doi.org/10.5890/DNC.2014.09.002
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Abstract

With online publication and social media taking the main role in dissemination of news, and with the decline of traditional printed media, it has become necessary to devise ways to automatically extract meaningful information from the plethora of sources available and to make that information readily available to interested parties. In this paper we present a method of automated analysis of the underlying structure of online newspapers based on Q-analysis and modularity optimisation. We show how the combination of the two strategies allows for the identification of well defined news clusters that are free of noise (unrelated stories) and provide automated clustering of information on trending topics on news published online.

Item Type: Journal Item
Copyright Holders: 2012 L&H Scientific Publishing, LLC.
ISSN: 2164-6414
Extra Information: DOI : 10.5890/DNC.2012.02.001
Keywords: Q-analysis; community detection; online news; topic modelling
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 40947
Depositing User: David Rodrigues
Date Deposited: 29 Apr 2015 15:53
Last Modified: 14 Sep 2017 16:23
URI: http://oro.open.ac.uk/id/eprint/40947
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