X-OODM:Leveraging Explainable Object-Oriented Design Methodology for Multi-Domain Sentiment Analysis  

作　　者：Abqa Javed Muhammad Shoaib Abdul Jaleel Mohamed Deriche Sharjeel Nawaz 

机构地区：[1]Department of Computer Science,University of Engineering and Technology,Lahore,54890,Pakistan [2]Department of Computer Science(RCET Campus,GRW),University of Engineering and Technology,Lahore,52250,Pakistan [3]Artificial Intelligence Centre(AIRC),Ajman University,Ajman,346,United Arab Emirates [4]Smith School of Business,University of Maryland,College Park,MD 20742-5151,USA

出　　处：《Computers, Materials & Continua》2025年第3期4977-4994,共18页计算机、材料和连续体(英文)

基　　金：support of the Deanship of Research and Graduate Studies at Ajman University under Projects 2024-IRG-ENiT-36 and 2024-IRG-ENIT-29.

摘　　要：Incorporation of explainability features in the decision-making web-based systems is considered a primary concern to enhance accountability,transparency,and trust in the community.Multi-domain Sentiment Analysis is a significant web-based system where the explainability feature is essential for achieving user satisfaction.Conventional design methodologies such as object-oriented design methodology(OODM)have been proposed for web-based application development,which facilitates code reuse,quantification,and security at the design level.However,OODM did not provide the feature of explainability in web-based decision-making systems.X-OODM modifies the OODM with added explainable models to introduce the explainability feature for such systems.This research introduces an explainable model leveraging X-OODM for designing transparent applications for multidomain sentiment analysis.The proposed design is evaluated using the design quality metrics defined for the evaluation of the X-OODM explainable model under user context.The design quality metrics,transferability,simulatability,informativeness,and decomposability were introduced one after another over time to the evaluation of the X-OODM user context.Auxiliary metrics of accessibility and algorithmic transparency were added to increase the degree of explainability for the design.The study results reveal that introducing such explainability parameters with X-OODM appropriately increases system transparency,trustworthiness,and user understanding.The experimental results validate the enhancement of decision-making for multi-domain sentiment analysis with integration at the design level of explainability.Future work can be built in this direction by extending this work to apply the proposed X-OODM framework over different datasets and sentiment analysis applications to further scrutinize its effectiveness in real-world scenarios.

关 键 词：Measurable explainable web-based application object-oriented design sentiment analysis MULTI-DOMAIN 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]