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Exploring the use of paragraph-level annotations for sentiment analysis of financial blogs

Ferguson, Paul, O'Hare, Neil, Davy, Michael, Bermingham, Adam, Sheridan, Páraic, Gurrin, Cathal orcid logoORCID: 0000-0003-4395-7702 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2009) Exploring the use of paragraph-level annotations for sentiment analysis of financial blogs. In: WOMAS 2009 - Workshop on Opinion Mining and Sentiment Analysis, 13 November 2009, Seville, Spain.

In this paper we describe our work in the area of topic-based sentiment analysis in the domain of financial blogs. We explore the use of paragraph-level and document-level annotations, examining how additional information from paragraph-level annotations can be used to increase the accuracy of document-level sentiment classification. We acknowledge the additional effort required to provide these paragraph-level annotations, and so we compare these findings against an automatic means of generating topic-specific sub-documents.
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Uncontrolled Keywords:sentiment analysis; opinion mining;
Subjects:Computer Science > Machine learning
Computer Science > Information storage and retrieval systems
Computer Science > World Wide Web
Computer Science > Information retrieval
DCU Faculties and Centres:Research Institutes and Centres > Centre for Digital Video Processing (CDVP)
Research Institutes and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > CLARITY: The Centre for Sensor Web Technologies
Official URL:http://sites.google.com/site/womsa09/
Copyright Information:© 2009 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Enterprise Ireland grant IP/2008/0549., Science Foundation Ireland grant 07/CE/I1147
ID Code:14934
Deposited On:13 Oct 2009 12:06 by Paul Ferguson . Last Modified 05 Jan 2022 14:07

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