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| Paper Abstract and Keywords | ||
| Presentation | 2021-01-20 13:45 Evaluating the Robustness of Community Detection from Information Cascades under Imperfect Data Daiki Suzuki, Sho Tsugawa (Univ. of Tsukuba)  CQ2020-68 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Community detection in a social network is an important topic in the network science research field. In this paper, we evaluate the robustness of a community detection algorithm using information diffusion cascades against deletion of the diffusion cascades. In the existing studies, the robustness of community detection algorithms against random missing cascades has been evaluated. In contrast, in this paper, we evaluate the robustness of community detection against biased missing data where the cascades of a certain amount of users are not available. Through experiments utilizing diffusion cascades on Twitter and synthetic diffusion cascades, we evaluate the effectiveness of the existing community detection algorithm called CosineSim under imperfect diffusion cascades. Consequently, we show that even when the diffusion cascades of 10% users are missing, the CosineSim achieves as high community detection accuracy as when the complete diffusion cascades are available. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | social networks / community detection / information diffusion / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 314, CQ2020-68, pp. 43-48, Jan. 2021. | |
| Paper # | CQ2020-68 | |
| Date of Issue | 2021-01-13 (CQ) | |
| 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 | CQ2020-68 |
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| Conference Information | |
| Committee | CQ CBE |
| Conference Date | 2021-01-20 - 2021-01-22 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | AR/VR, Broadcasting Service, Video/Voice Services Quality, High Realistic, User Behavior/Psychology, User Experience, Media Quality, Network Quality and QoS Control, Networks and Communications at Disaster, User Behavior, Machine Learning, Video Communication, etc. |
| Paper Information | |
| Registration To | CQ |
| Conference Code | 2021-01-CQ-CBE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Evaluating the Robustness of Community Detection from Information Cascades under Imperfect Data |
| Sub Title (in English) | |
| Keyword(1) | social networks |
| Keyword(2) | community detection |
| Keyword(3) | information diffusion |
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| 1st Author's Name | Daiki Suzuki |
| 1st Author's Affiliation | University of Tsukuba (Univ. of Tsukuba) |
| 2nd Author's Name | Sho Tsugawa |
| 2nd Author's Affiliation | University of Tsukuba (Univ. of Tsukuba) |
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| Speaker | Author-1 |
| Date Time | 2021-01-20 13:45:00 |
| Presentation Time | 20 minutes |
| Registration for | CQ |
| Paper # | CQ2020-68 |
| Volume (vol) | vol.120 |
| Number (no) | no.314 |
| Page | pp.43-48 |
| #Pages | 6 |
| Date of Issue | 2021-01-13 (CQ) |
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