Fostering Explainable Online Review Assessment Through Computational Argumentation

A.K. Zafarghandi; D. Ceolin

Fostering Explainable Online Review Assessment Through Computational Argumentation

A.K. Zafarghandi
, D. Ceolin

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

Abstract

Explainable methods have received increased attention within artificial intelligence. Wherever an automated system makes a decision an explanation is required to convince a user about the decision. Furthermore, online information quality assessment is crucial to help users navigate information. However, explaining the assessment of online information had not been clarified well. The current work provides explanations to a user about the assessment of online information and specific, provides explanations for the quality assessments of online reviews. We construct an abstract argumentation framework (AF) based on a set of given reviews. We consider the grounded semantics of AFs to assess each topic. Then, we discuss the question of why a score can be assigned to a topic of a product. Furthermore, we indicate a proper score of a review based on the scores of topics within the review in question. We also collect arguments that can support the chosen score of a review.

Original language	English
Title of host publication	ArgXAI 2022 Argumentation for eXplainable AI
Subtitle of host publication	1st International Workshop on Argumentation for eXplainable AI, co-located with 9th International Conference on Computational Models of Argument (COMMA 2022) Cardiff, Wales, September 12, 2022
Editors	K. Cyras, T. Kampik, O. Cocarascu, A. Rago
Publisher	CEUR Workshop Proceedings
Pages	1-12
Number of pages	12
Publication status	Published - 2022
Externally published	Yes
Event	1st International Workshop on Argumentation for eXplainable AI, ArgXAI 2022 - Cardiff, United Kingdom Duration: 12 Sept 2022 → …

Publication series

Name	CEUR Workshop Proceedings
Publisher	CEUR-WS
Volume	3209
ISSN (Print)	1613-0073

Conference

Conference	1st International Workshop on Argumentation for eXplainable AI, ArgXAI 2022
Country/Territory	United Kingdom
City	Cardiff
Period	12/09/22 → …

Funding

This research has been supported by the Centrum Wiskunde & Informatica (CWI) and Supported by the Netherlands eScience Center project “The Eye of the Beholder” (project nr. 027.020.15). Acknowledgments This research has been supported by the Centrum Wiskunde & Informat-ica (CWI) and Supported by the Netherlands eScience Center project “The Eye of the Beholder” (project nr. 027.020.15).

Funders	Funder number
Centrum Wiskunde & Informat-ica
Centrum Wiskunde and Informatica	027.020.15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

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https://ceur-ws.org/Vol-3209/8546.pdf

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Zafarghandi, A. K., & Ceolin, D. (2022). Fostering Explainable Online Review Assessment Through Computational Argumentation. In K. Cyras, T. Kampik, O. Cocarascu, & A. Rago (Eds.), ArgXAI 2022 Argumentation for eXplainable AI: 1st International Workshop on Argumentation for eXplainable AI, co-located with 9th International Conference on Computational Models of Argument (COMMA 2022) Cardiff, Wales, September 12, 2022 (pp. 1-12). (CEUR Workshop Proceedings; Vol. 3209). CEUR Workshop Proceedings. https://ceur-ws.org/Vol-3209/8546.pdf

Zafarghandi, A.K. ; Ceolin, D. / Fostering Explainable Online Review Assessment Through Computational Argumentation. ArgXAI 2022 Argumentation for eXplainable AI: 1st International Workshop on Argumentation for eXplainable AI, co-located with 9th International Conference on Computational Models of Argument (COMMA 2022) Cardiff, Wales, September 12, 2022. editor / K. Cyras ; T. Kampik ; O. Cocarascu ; A. Rago. CEUR Workshop Proceedings, 2022. pp. 1-12 (CEUR Workshop Proceedings).

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title = "Fostering Explainable Online Review Assessment Through Computational Argumentation",

abstract = "Explainable methods have received increased attention within artificial intelligence. Wherever an automated system makes a decision an explanation is required to convince a user about the decision. Furthermore, online information quality assessment is crucial to help users navigate information. However, explaining the assessment of online information had not been clarified well. The current work provides explanations to a user about the assessment of online information and specific, provides explanations for the quality assessments of online reviews. We construct an abstract argumentation framework (AF) based on a set of given reviews. We consider the grounded semantics of AFs to assess each topic. Then, we discuss the question of why a score can be assigned to a topic of a product. Furthermore, we indicate a proper score of a review based on the scores of topics within the review in question. We also collect arguments that can support the chosen score of a review.",

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Zafarghandi, AK & Ceolin, D 2022, Fostering Explainable Online Review Assessment Through Computational Argumentation. in K Cyras, T Kampik, O Cocarascu & A Rago (eds), ArgXAI 2022 Argumentation for eXplainable AI: 1st International Workshop on Argumentation for eXplainable AI, co-located with 9th International Conference on Computational Models of Argument (COMMA 2022) Cardiff, Wales, September 12, 2022. CEUR Workshop Proceedings, vol. 3209, CEUR Workshop Proceedings, pp. 1-12, 1st International Workshop on Argumentation for eXplainable AI, ArgXAI 2022, Cardiff, United Kingdom, 12/09/22. <https://ceur-ws.org/Vol-3209/8546.pdf>

Fostering Explainable Online Review Assessment Through Computational Argumentation. / Zafarghandi, A.K.; Ceolin, D.
ArgXAI 2022 Argumentation for eXplainable AI: 1st International Workshop on Argumentation for eXplainable AI, co-located with 9th International Conference on Computational Models of Argument (COMMA 2022) Cardiff, Wales, September 12, 2022. ed. / K. Cyras; T. Kampik; O. Cocarascu; A. Rago. CEUR Workshop Proceedings, 2022. p. 1-12 (CEUR Workshop Proceedings; Vol. 3209).

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

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AU - Zafarghandi, A.K.

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AB - Explainable methods have received increased attention within artificial intelligence. Wherever an automated system makes a decision an explanation is required to convince a user about the decision. Furthermore, online information quality assessment is crucial to help users navigate information. However, explaining the assessment of online information had not been clarified well. The current work provides explanations to a user about the assessment of online information and specific, provides explanations for the quality assessments of online reviews. We construct an abstract argumentation framework (AF) based on a set of given reviews. We consider the grounded semantics of AFs to assess each topic. Then, we discuss the question of why a score can be assigned to a topic of a product. Furthermore, we indicate a proper score of a review based on the scores of topics within the review in question. We also collect arguments that can support the chosen score of a review.

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Zafarghandi AK, Ceolin D. Fostering Explainable Online Review Assessment Through Computational Argumentation. In Cyras K, Kampik T, Cocarascu O, Rago A, editors, ArgXAI 2022 Argumentation for eXplainable AI: 1st International Workshop on Argumentation for eXplainable AI, co-located with 9th International Conference on Computational Models of Argument (COMMA 2022) Cardiff, Wales, September 12, 2022. CEUR Workshop Proceedings. 2022. p. 1-12. (CEUR Workshop Proceedings). Epub 2022 Sept 11.

Fostering Explainable Online Review Assessment Through Computational Argumentation

Abstract

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UN SDGs

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