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Paper Abstract and Keywords
Presentation 2025-10-02 13:05
Identifying Influential Users in Dynamic Social Graphs on Bluesky Using Graph-Based Representation Learning
Shinnosuke Boyama, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) SIS2025-27
Abstract (in Japanese) (See Japanese page) 
(in English) Understanding how information propagates and optimising marketing strategies requires identifying influential users on social media. In rapidly growing social networks such as Bluesky, effective prediction methods for identifying influential users within dynamically changing network structures are essential. This paper presents a new method for identifying and predicting influential users in evolving social networks, combining ordinal regression learning with dynamic graph neural networks. Unlike conventional binary classification methods, our approach categorises influence into three hierarchical levels — non-influential, moderately influential, and highly influential — and explicitly learns the ordinal relationships between these categories. Additionally, we use a rolling window approach to capture long-term temporal dependencies and address the dynamic characteristics of emerging social networks. Experimental results on the BlueTempNet dataset show that our method outperforms conventional baseline methods, especially in predicting influential new users, achieving improvements of up to 6.36 points in AUPRC scores.
Keyword (in Japanese) (See Japanese page) 
(in English) graph neural network / dynamic graph / social network / ordinal regression / prediction / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 191, SIS2025-27, pp. 17-22, Oct. 2025.
Paper # SIS2025-27 
Date of Issue 2025-09-25 (SIS) 
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 SIS2025-27

Conference Information
Committee ITE-BCT SIS  
Conference Date 2025-10-02 - 2025-10-03 
Place (in Japanese) (See Japanese page) 
Place (in English) FUKUI SENKYO bldg. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SIS 
Conference Code 2025-10-BCT-SIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Identifying Influential Users in Dynamic Social Graphs on Bluesky Using Graph-Based Representation Learning 
Sub Title (in English)  
Keyword(1) graph neural network  
Keyword(2) dynamic graph  
Keyword(3) social network  
Keyword(4) ordinal regression  
Keyword(5) prediction  
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1st Author's Name Shinnosuke Boyama  
1st Author's Affiliation Kansai University (Kansai Univ.)
2nd Author's Name Soh Yoshida  
2nd Author's Affiliation Kansai University (Kansai Univ.)
3rd Author's Name Mitsuji Muneyasu  
3rd Author's Affiliation Kansai University (Kansai Univ.)
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Speaker Author-1 
Date Time 2025-10-02 13:05:00 
Presentation Time 20 minutes 
Registration for SIS 
Paper # SIS2025-27 
Volume (vol) vol.125 
Number (no) no.191 
Page pp.17-22 
#Pages 6 
Date of Issue 2025-09-25 (SIS) 

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