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Paper Abstract and Keywords
Presentation 2020-06-05 13:25
Analysis of influence of network structure on information diffusion
Luyan XU, Kazuya Sawada (TUS), Yutaka Shimada (SU), Tohru Ikeguchi (TUS) NLP2020-15 CCS2020-5
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose an information diffusion model with eigenvector centrality. Using the proposed model, we investigated the relationship between the influence of information and the final diffusion rates on regular and random networks, when we change the influence of information.
Next, we investigated the relationship between the influence of information and the average spreading speed on regular and random networks, when we change the influence of information.
As a result, we found that the final diffusion rates on regular network are higher than those on random networks. When the influence of information increases, the difference of the final diffusion rates between regular and random networks increases to a peak value, and finally converges to a small value.
On the other hand, when information spreads to the entire network, we found that the average spreading speed on random networks is faster than that on regular networks. In addition, the difference of the average spreading speed between regular and random networks increases with the influence of information.
Keyword (in Japanese) (See Japanese page) 
(in English) Information diffusion / Complex network / Mathematical model / Network centrality / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 55, NLP2020-15, pp. 23-26, June 2020.
Paper # NLP2020-15 
Date of Issue 2020-05-29 (NLP, CCS) 
ISSN Online edition: ISSN 2432-6380
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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)
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Conference Information
Committee CCS NLP  
Conference Date 2020-06-05 - 2020-06-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NLP 
Conference Code 2020-06-CCS-NLP 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis of influence of network structure on information diffusion 
Sub Title (in English)  
Keyword(1) Information diffusion  
Keyword(2) Complex network  
Keyword(3) Mathematical model  
Keyword(4) Network centrality  
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1st Author's Name Luyan XU  
1st Author's Affiliation Tokyo University of Science (TUS)
2nd Author's Name Kazuya Sawada  
2nd Author's Affiliation Tokyo University of Science (TUS)
3rd Author's Name Yutaka Shimada  
3rd Author's Affiliation Saitama University (SU)
4th Author's Name Tohru Ikeguchi  
4th Author's Affiliation Tokyo University of Science (TUS)
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Speaker Author-1 
Date Time 2020-06-05 13:25:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2020-15, CCS2020-5 
Volume (vol) vol.120 
Number (no) no.55(NLP), no.56(CCS) 
Page pp.23-26 
#Pages
Date of Issue 2020-05-29 (NLP, CCS) 


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