Measuring the semantic uncertainty of news events for evolution potential estimation

Luo, X; Xuan, J; Lu, J; Zhang, G

Measuring the semantic uncertainty of news events for evolution potential estimation

Luo, X Xuan, J

Lu, J

Zhang, G

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Publication Type:: Journal Article
Citation:: ACM Transactions on Information Systems, 2016, 34 (4)
Issue Date:: 2016-06-01

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Field	Value	Language
dc.contributor.author	Luo, X	en_US
dc.contributor.author	Xuan, J https://orcid.org/0000-0002-8367-6908	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.date.issued	2016-06-01	en_US
dc.identifier.citation	ACM Transactions on Information Systems, 2016, 34 (4)	en_US
dc.identifier.issn	1046-8188	en_US
dc.identifier.uri	http://hdl.handle.net/10453/122810
dc.description.abstract	© 2016 ACM. The evolution potential estimation of news events can support the decision making of both corporations and governments. For example, a corporation could manage its public relations crisis in a timely manner if a negative news event about this corporation is known with large evolution potential in advance. However, existing state-of-the-art methods are mainly based on time series historical data, which are not suitable for the news events with limited historical data and bursty properties. In this article, we propose a purely content-based method to estimate the evolution potential of the news events. The proposed method considers a news event at a given time point as a system composed of different keywords, and the uncertainty of this system is defined and measured as the Semantic Uncertainty of this news event. At the same time, an uncertainty space is constructed with two extreme states: the most uncertain state and the most certain state. We believe that the Semantic Uncertainty has correlation with the content evolution of the news events, so it can be used to estimate the evolution potential of the news events. In order to verify the proposed method, we present detailed experimental setups and results measuring the correlation of the Semantic Uncertainty with the Content Change of news events using collected news events data. The results show that the correlation does exist and is stronger than the correlation of value from the time-series-based method with the Content Change. Therefore, we can use the Semantic Uncertainty to estimate the evolution potential of news events.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP140101366
dc.relation.ispartof	ACM Transactions on Information Systems	en_US
dc.relation.isbasedon	10.1145/2903719	en_US
dc.subject.classification	Information Systems	en_US
dc.title	Measuring the semantic uncertainty of news events for evolution potential estimation	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	34	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	0807 Library and Information Studies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	open_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	34	en_US

Abstract:

© 2016 ACM. The evolution potential estimation of news events can support the decision making of both corporations and governments. For example, a corporation could manage its public relations crisis in a timely manner if a negative news event about this corporation is known with large evolution potential in advance. However, existing state-of-the-art methods are mainly based on time series historical data, which are not suitable for the news events with limited historical data and bursty properties. In this article, we propose a purely content-based method to estimate the evolution potential of the news events. The proposed method considers a news event at a given time point as a system composed of different keywords, and the uncertainty of this system is defined and measured as the Semantic Uncertainty of this news event. At the same time, an uncertainty space is constructed with two extreme states: the most uncertain state and the most certain state. We believe that the Semantic Uncertainty has correlation with the content evolution of the news events, so it can be used to estimate the evolution potential of the news events. In order to verify the proposed method, we present detailed experimental setups and results measuring the correlation of the Semantic Uncertainty with the Content Change of news events using collected news events data. The results show that the correlation does exist and is stronger than the correlation of value from the time-series-based method with the Content Change. Therefore, we can use the Semantic Uncertainty to estimate the evolution potential of news events.

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http://hdl.handle.net/10453/122810