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Conference papers
Implicit and Explicit Aspect Extraction in Financial Microblogs
Abstract : This paper focuses on aspect extraction which is a sub-task of Aspect-based Sentiment Analysis. The goal is to report an extraction method of financial aspects in microblog messages. Our approach uses a stock-investment taxonomy for the identification of explicit and implicit aspects. We compare supervised and unsupervised methods to assign predefined categories at message level. Results on 7 aspect classes show 0.71 accuracy, while the 32 class classification gives 0.82 accuracy for messages containing explicit aspects and 0.35 for implicit aspects.
Cited literature [32 references]
https://hal.univ-rennes2.fr/hal-02280371
Contributor : Laurence Leroux <>
Submitted on : Tuesday, September 10, 2019 - 3:22:03 PM
Last modification on : Monday, January 20, 2020 - 3:24:05 PM
Document(s) archivé(s) le : Friday, February 7, 2020 - 6:44:42 PM
Contributor : Laurence Leroux <>
Submitted on : Tuesday, September 10, 2019 - 3:22:03 PM
Last modification on : Monday, January 20, 2020 - 3:24:05 PM
Document(s) archivé(s) le : Friday, February 7, 2020 - 6:44:42 PM
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W18-3108.pdf
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