Extraction of Temporal Networks from Term Co-Occurrences in Online Textual Sources
Marko Popović,
Hrvoje Štefančić,
Borut Sluban,
Petra Kralj Novak,
Miha Grčar,
Igor Mozetič,
Michelangelo Puliga and
Vinko Zlatić
PLOS ONE, 2014, vol. 9, issue 12, 1-29
Abstract:
A stream of unstructured news can be a valuable source of hidden relations between different entities, such as financial institutions, countries, or persons. We present an approach to continuously collect online news, recognize relevant entities in them, and extract time-varying networks. The nodes of the network are the entities, and the links are their co-occurrences. We present a method to estimate the significance of co-occurrences, and a benchmark model against which their robustness is evaluated. The approach is applied to a large set of financial news, collected over a period of two years. The entities we consider are 50 countries which issue sovereign bonds, and which are insured by Credit Default Swaps (CDS) in turn. We compare the country co-occurrence networks to the CDS networks constructed from the correlations between the CDS. The results show relatively small, but significant overlap between the networks extracted from the news and those from the CDS correlations.
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0099515 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 99515&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0099515
DOI: 10.1371/journal.pone.0099515
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().