Tracking information flow between primary and secondary news sources

Authors:
Will Radford;Ben Hachey;James R. Curran;Maria Milosavljevic
Affiliations:
University of Sydney, NSW, Australia and Capital Markets CRC, NSW, Australia;University of Sydney, NSW, Australia and Macquarie University, NSW, Australia;University of Sydney, NSW, Australia and Capital Markets CRC, NSW, Australia;Macquarie University, NSW, Australia
Venue:
WSA '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a World of Social Media
Year:
2010

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Similarity measures for tracking information flow

Proceedings of the 14th ACM international conference on Information and knowledge management

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Abstract

Tracking information flow (IFLOW) is crucial to understanding the evolution of news stories. We present analysis and experiments for IFLOW between company announcements and newswire. Error analysis shows that many FPs are annotation errors and many FNs are due to coarse-grained document-level modelling. Experiments show that document meta-data features (e.g., category, length, timing) improve f-scores relative to upper bound by 23%.