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Titlebook: Applications of Social Media and Social Network Analysis; Przemys?aw Kazienko,Nitesh Chawla Book 2015 Springer International Publishing Sw

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發(fā)表于 2025-3-23 12:23:30 | 只看該作者
Indifferent Attachment: The Role of Degree in Ranking Friends,f ranks within the Top Friends (e.g., #1-versus-#3, #2-versus-#3, ...) also reveal no marked preference for a popular friend over a less popular one; in fact, there is some evidence that individuals tend to prefer less popular friends over more popular ones. To the extent that ranking decisions form
12#
發(fā)表于 2025-3-23 14:02:55 | 只看該作者
13#
發(fā)表于 2025-3-23 19:18:38 | 只看該作者
Studying Graph Dynamics Through Intrinsic Time Based Diffusion Analysis,epts is easily understandable yet completely new in the study of diffusion phenomena. We experiment our approach on three real datasets and show the promising results of intrinsic time-based diffusion analysis.
14#
發(fā)表于 2025-3-24 01:49:24 | 只看該作者
15#
發(fā)表于 2025-3-24 02:43:31 | 只看該作者
Social Network Analysis for Biometric Template Protection,one. Social network based feature analysis confirms the domain transformation. It is computationally very hard to regenerate the original features from the social network matric value. This domain transformation confirms the cancelability in biometric template generation. To ensure the multi-level c
16#
發(fā)表于 2025-3-24 08:05:31 | 只看該作者
Applications of Social Media and Social Network Analysis
17#
發(fā)表于 2025-3-24 11:30:39 | 只看該作者
Applications of Social Media and Social Network Analysis978-3-319-19003-7Series ISSN 2190-5428 Series E-ISSN 2190-5436
18#
發(fā)表于 2025-3-24 16:08:13 | 只看該作者
19#
發(fā)表于 2025-3-24 20:01:05 | 只看該作者
Lecture Notes in Social Networkshttp://image.papertrans.cn/a/image/159563.jpg
20#
發(fā)表于 2025-3-24 23:21:23 | 只看該作者
https://doi.org/10.1007/978-3-662-48893-5trinsic and extrinsic consensus (voting) among neighboring users influenced by the network topology. We introduce an algorithm that considers the degree information of nodes (users) to model how reputations spread within the network. In our algorithm, each node updates reputations about its neighbor
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