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Paper Abstract and Keywords
Presentation 2026-07-24 11:15
Supporting the Understanding of Accessibility Violation Using User Reviews
Ryoya Koyama (Science Tokyo), Zhiyao Wang (UOsaka), Jialong Li (Waseda Univ.), Tatsuhiro Tsuchiya (UOsaka), Kenji Tei (Science Tokyo) SS2026-30 KBSE2026-30
Abstract (in Japanese) (See Japanese page) 
(in English) In mobile app accessibility testing, automated tools such as Google Accessibility Scanner can detect typical violations; however, their outputs are often limited to low-level technical information, making it difficult to intuitively understand the actual impact on users. This study proposes a method to enrich automated accessibility reports by attaching real user reviews, and evaluates its effectiveness in improving the understanding of accessibility violations. We construct a pipeline that extracts candidate reviews based on similarity and keyword matching, and then selects representative reviews using a large language model (LLM). The method is evaluated on four applications and three types of violations: Touch Target, Item Label, and Text Contrast.
The results show that only 14 out of 60 selected reviews clearly correspond to the target violations, with substantial variation across violation types. Nevertheless, reports augmented with user reviews consistently outperform baseline reports in clarity, empathy, persuasiveness, urgency, and cognitive load, significantly improving the understanding of user impact.
Keyword (in Japanese) (See Japanese page) 
(in English) Accessibility / Mobile Applications / User Reviews / Automated Testing / Large Language Models / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 126, KBSE2026-30, pp. 173-178, July 2026.
Paper # KBSE2026-30 
Date of Issue 2026-07-15 (SS, KBSE) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SS2026-30 KBSE2026-30

Conference Information
Committee SS KBSE IPSJ-SE  
Conference Date 2026-07-22 - 2026-07-24 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To KBSE 
Conference Code 2026-07-SS-KBSE-SE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Supporting the Understanding of Accessibility Violation Using User Reviews 
Sub Title (in English)  
Keyword(1) Accessibility  
Keyword(2) Mobile Applications  
Keyword(3) User Reviews  
Keyword(4) Automated Testing  
Keyword(5) Large Language Models  
Keyword(6)  
Keyword(7)  
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1st Author's Name Ryoya Koyama  
1st Author's Affiliation Institute of Science Tokyo (Science Tokyo)
2nd Author's Name Zhiyao Wang  
2nd Author's Affiliation The University of Osaka (UOsaka)
3rd Author's Name Jialong Li  
3rd Author's Affiliation Waseda University (Waseda Univ.)
4th Author's Name Tatsuhiro Tsuchiya  
4th Author's Affiliation The University of Osaka (UOsaka)
5th Author's Name Kenji Tei  
5th Author's Affiliation Institute of Science Tokyo (Science Tokyo)
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Speaker Author-1 
Date Time 2026-07-24 11:15:00 
Presentation Time 20 minutes 
Registration for KBSE 
Paper # SS2026-30, KBSE2026-30 
Volume (vol) vol.126 
Number (no) no.125(SS), no.126(KBSE) 
Page pp.173-178 
#Pages 6 
Date of Issue 2026-07-15 (SS, KBSE) 

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