Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance

Yung Chun Chang; Cen Chieh Chen; Yu Lun Hsieh; Chien Chin Chen; Wen Lian Hsu

Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance

Yung Chun Chang, Cen Chieh Chen, Yu Lun Hsieh, Chien Chin Chen, Wen Lian Hsu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we propose a flexible principle-based approach (PBA) for reader-emotion classification and writing assistance. PBA is a highly automated process that learns emotion templates from raw texts to characterize an emotion and is comprehensible for humans. These templates are adopted to predict reader-emotion, and may further assist in emotional resonance writing. Results demonstrate that PBA can effectively detect reader-emotions by exploiting the syntactic structures and semantic associations in the context, thus outperforming wellknown statistical text classification methods and the state-of-the-art reader-emotion classification method. Moreover, writers are able to create more emotional resonance in articles under the assistance of the generated emotion templates. These templates have been proven to be highly interpretable, which is an attribute that is difficult to accomplish in traditional statistical methods.

Original language	English
Title of host publication	ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference
Publisher	Association for Computational Linguistics (ACL)
Pages	775-780
Number of pages	6
Volume	2
ISBN (Electronic)	9781941643730
Publication status	Published - 2015
Externally published	Yes
Event	53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015 - Beijing, China Duration: Jul 26 2015 → Jul 31 2015

Conference

Conference	53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015
Country/Territory	China
City	Beijing
Period	7/26/15 → 7/31/15

ASJC Scopus subject areas

Artificial Intelligence
Software
Language and Linguistics
Linguistics and Language

Cite this

Chang, Y. C., Chen, C. C., Hsieh, Y. L., Chen, C. C., & Hsu, W. L. (2015). Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance. In ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference (Vol. 2, pp. 775-780). Association for Computational Linguistics (ACL).

Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance. / Chang, Yung Chun; Chen, Cen Chieh; Hsieh, Yu Lun et al.
ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference. Vol. 2 Association for Computational Linguistics (ACL), 2015. p. 775-780.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chang, YC, Chen, CC, Hsieh, YL, Chen, CC & Hsu, WL 2015, Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance. in ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference. vol. 2, Association for Computational Linguistics (ACL), pp. 775-780, 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015, Beijing, China, 7/26/15.

Chang YC, Chen CC, Hsieh YL, Chen CC, Hsu WL. Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance. In ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference. Vol. 2. Association for Computational Linguistics (ACL). 2015. p. 775-780

Chang, Yung Chun ; Chen, Cen Chieh ; Hsieh, Yu Lun et al. / Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance. ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference. Vol. 2 Association for Computational Linguistics (ACL), 2015. pp. 775-780

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abstract = "In this paper, we propose a flexible principle-based approach (PBA) for reader-emotion classification and writing assistance. PBA is a highly automated process that learns emotion templates from raw texts to characterize an emotion and is comprehensible for humans. These templates are adopted to predict reader-emotion, and may further assist in emotional resonance writing. Results demonstrate that PBA can effectively detect reader-emotions by exploiting the syntactic structures and semantic associations in the context, thus outperforming wellknown statistical text classification methods and the state-of-the-art reader-emotion classification method. Moreover, writers are able to create more emotional resonance in articles under the assistance of the generated emotion templates. These templates have been proven to be highly interpretable, which is an attribute that is difficult to accomplish in traditional statistical methods.",

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Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance

Abstract

Conference

ASJC Scopus subject areas

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