ABSApp: A portable weakly-supervised aspect-based sentiment extraction system

Oren Pereg; Daniel Korat; Moshe Wasserblat; Jonathan Mamou; Ido Dagan

doi:10.18653/v1/D19-3001

ABSApp: A portable weakly-supervised aspect-based sentiment extraction system

Oren Pereg
, Daniel Korat
, Moshe Wasserblat
, Jonathan Mamou
, Ido Dagan

Department of Computer Science and Artificial Intelligence

Intel

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

7 Scopus citations

Abstract

We present ABSApp, a portable system for weakly-supervised aspect-based sentiment extraction ¹. The system is interpretable and user friendly and does not require labeled training data, hence can be rapidly and cost-effectively used across different domains in applied setups. The system flow includes three stages: First, it generates domain-specific aspect and opinion lexicons based on an unlabeled dataset; second, it enables the user to view and edit those lexicons (weak supervision); and finally, it enables the user to select an unlabeled target dataset from the same domain, classify it, and generate an aspect-based sentiment report. ABSApp has been successfully used in a number of real-life use cases, among them movie review analysis and convention impact analysis.

Original language	English
Title of host publication	EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations
Publisher	Association for Computational Linguistics (ACL)
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781950737925
DOIs	https://doi.org/10.18653/v1/D19-3001
State	Published - 2019
Event	2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstration, EMNLP-IJCNLP 2019 - Hong Kong, China Duration: 3 Nov 2019 → 7 Nov 2019

Publication series

Name	EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations

Conference

Conference	2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstration, EMNLP-IJCNLP 2019
Country/Territory	China
City	Hong Kong
Period	3/11/19 → 7/11/19

Bibliographical note

Publisher Copyright:
© 2019 Association for Computational Linguistics.

Access to Document

10.18653/v1/D19-3001

Cite this

Pereg, O., Korat, D., Wasserblat, M., Mamou, J., & Dagan, I. (2019). ABSApp: A portable weakly-supervised aspect-based sentiment extraction system. In EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations (pp. 1-6). (EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/D19-3001

Pereg, Oren ; Korat, Daniel ; Wasserblat, Moshe et al. / ABSApp : A portable weakly-supervised aspect-based sentiment extraction system. EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations. Association for Computational Linguistics (ACL), 2019. pp. 1-6 (EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations).

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abstract = "We present ABSApp, a portable system for weakly-supervised aspect-based sentiment extraction 1. The system is interpretable and user friendly and does not require labeled training data, hence can be rapidly and cost-effectively used across different domains in applied setups. The system flow includes three stages: First, it generates domain-specific aspect and opinion lexicons based on an unlabeled dataset; second, it enables the user to view and edit those lexicons (weak supervision); and finally, it enables the user to select an unlabeled target dataset from the same domain, classify it, and generate an aspect-based sentiment report. ABSApp has been successfully used in a number of real-life use cases, among them movie review analysis and convention impact analysis.",

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note = "Publisher Copyright: {\textcopyright} 2019 Association for Computational Linguistics.; 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstration, EMNLP-IJCNLP 2019 ; Conference date: 03-11-2019 Through 07-11-2019",

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Pereg, O, Korat, D, Wasserblat, M, Mamou, J & Dagan, I 2019, ABSApp: A portable weakly-supervised aspect-based sentiment extraction system. in EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations. EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations, Association for Computational Linguistics (ACL), pp. 1-6, 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstration, EMNLP-IJCNLP 2019, Hong Kong, China, 3/11/19. https://doi.org/10.18653/v1/D19-3001

ABSApp: A portable weakly-supervised aspect-based sentiment extraction system. / Pereg, Oren; Korat, Daniel; Wasserblat, Moshe et al.
EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations. Association for Computational Linguistics (ACL), 2019. p. 1-6 (EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations).

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

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Pereg O, Korat D, Wasserblat M, Mamou J, Dagan I. ABSApp: A portable weakly-supervised aspect-based sentiment extraction system. In EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations. Association for Computational Linguistics (ACL). 2019. p. 1-6. (EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations). doi: 10.18653/v1/D19-3001

ABSApp: A portable weakly-supervised aspect-based sentiment extraction system

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