research-article

Explainable Artificial Intelligence-Based Competitive Factor Identification

Authors:

Younghoon LeeAuthors Info & Claims

ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 16, Issue 1

Article No.: 10, Pages 1 - 11

https://doi.org/10.1145/3451529

Published: 20 July 2021 Publication History

Abstract

Competitor analysis is an essential component of corporate strategy, providing both offensive and defensive strategic contexts to identify opportunities and threats. The rapid development of social media has recently led to several methodologies and frameworks facilitating competitor analysis through online reviews. Existing studies only focused on detecting comparative sentences in review comments or utilized low-performance models. However, this study proposes a novel approach to identifying the competitive factors using a recent explainable artificial intelligence approach at the comprehensive product feature level. We establish a model to classify the review comments for each corresponding product and evaluate the relevance of each keyword in such comments during the classification process. We then extract and prioritize the keywords and determine their competitiveness based on relevance. Our experiment results show that the proposed method can effectively extract the competitive factors both qualitatively and quantitatively.

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Cited By

Pandey UThakur SChaturvedi RJoshi B(2024)AI-Enabled Segmentation Targeting and Positioning (STP) in the Service IndustryIntegrating AI-Driven Technologies Into Service Marketing10.4018/979-8-3693-7122-0.ch004(65-86)Online publication date: 26-Jul-2024
https://doi.org/10.4018/979-8-3693-7122-0.ch004
Saarela MPodgorelec V(2024)Recent Applications of Explainable AI (XAI): A Systematic Literature ReviewApplied Sciences10.3390/app1419888414:19(8884)Online publication date: 2-Oct-2024
https://doi.org/10.3390/app14198884
Ye XSun YLiu DLi T(2023)A Multisource Data Fusion-based Heterogeneous Graph Attention Network for Competitor PredictionACM Transactions on Knowledge Discovery from Data10.1145/362510118:2(1-20)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3625101
Show More Cited By

Index Terms

Explainable Artificial Intelligence-Based Competitive Factor Identification
1. General and reference
  1. Cross-computing tools and techniques
    1. Reliability
2. Human-centered computing
  1. Ubiquitous and mobile computing

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Information

Published In

cover image ACM Transactions on Knowledge Discovery from Data

ACM Transactions on Knowledge Discovery from Data Volume 16, Issue 1

February 2022

475 pages

ISSN:1556-4681

EISSN:1556-472X

DOI:10.1145/3472794

Editor:
Charu Aggarwal
IBM T. J. Watson Research, USA

Issue’s Table of Contents

Copyright © 2021 Association for Computing Machinery.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 July 2021

Accepted: 01 February 2021

Revised: 01 January 2021

Received: 01 July 2020

Published in TKDD Volume 16, Issue 1

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National Research Foundation of Korea (NRF)
Korea government (MSIT)

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Cited By

Pandey UThakur SChaturvedi RJoshi B(2024)AI-Enabled Segmentation Targeting and Positioning (STP) in the Service IndustryIntegrating AI-Driven Technologies Into Service Marketing10.4018/979-8-3693-7122-0.ch004(65-86)Online publication date: 26-Jul-2024
https://doi.org/10.4018/979-8-3693-7122-0.ch004
Saarela MPodgorelec V(2024)Recent Applications of Explainable AI (XAI): A Systematic Literature ReviewApplied Sciences10.3390/app1419888414:19(8884)Online publication date: 2-Oct-2024
https://doi.org/10.3390/app14198884
Ye XSun YLiu DLi T(2023)A Multisource Data Fusion-based Heterogeneous Graph Attention Network for Competitor PredictionACM Transactions on Knowledge Discovery from Data10.1145/362510118:2(1-20)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3625101
Li KCui YLi WLv TYuan XLi SNi WSimsek MDressler F(2023)When Internet of Things Meets Metaverse: Convergence of Physical and Cyber WorldsIEEE Internet of Things Journal10.1109/JIOT.2022.323284510:5(4148-4173)Online publication date: 1-Mar-2023
https://doi.org/10.1109/JIOT.2022.3232845
Lee Y(2022)Identifying Competitive Attributes Based on an Ensemble of Explainable Artificial IntelligenceBusiness & Information Systems Engineering10.1007/s12599-021-00737-564:4(407-419)Online publication date: 14-Jan-2022
https://doi.org/10.1007/s12599-021-00737-5
Tu SHsu CLu Y(2021)Improving RE-SWOT Analysis with Sentiment Classification: A Case Study of Travel AgenciesFuture Internet10.3390/fi1309022613:9(226)Online publication date: 30-Aug-2021
https://doi.org/10.3390/fi13090226

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