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Automatic event-level textual emotion sensing using mutual action histogram between entities

Abstract : Automatic emotion sensing in textual data is crucial for the development of intelligent interfaces in many interactive computer applications. This paper describes a high-precision, knowledgebase-independent approach for automatic emotion sensing for the subjects of events embedded within sentences. The proposed approach is based on the probability distribution of common mutual actions between the subject and the object of an event. We have incorporated web-based text mining and semantic role labeling techniques, together with a number of reference entity pairs and hand-crafted emotion generation rules to realize an event emotion detection system. The evaluation outcome reveals a satisfactory result with about 85% accuracy for detecting the positive, negative and neutral emotions.
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https://hal.inria.fr/inria-00426567
Contributor : Samuel Cruz-Lara <>
Submitted on : Tuesday, October 27, 2009 - 10:35:27 AM
Last modification on : Friday, February 26, 2021 - 3:28:08 PM
Long-term archiving on: : Thursday, June 17, 2010 - 6:10:58 PM

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Cheng-Yu Lu, Shian-Hua Lin, Jen-Chang Liu, Samuel Cruz-Lara, Jen-Shin Hong. Automatic event-level textual emotion sensing using mutual action histogram between entities. Expert Systems with Applications, Elsevier, 2009, 37 (2), pp.1643-1653. ⟨10.1016/j.eswa.2009.06.099⟩. ⟨inria-00426567⟩

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