DeepIS: Susceptibility Estimation on Social Networks

Wenwen Xia, Yuchen Li, Jun Wu, Shenghong Li

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

Influence diffusion estimation is a crucial problem in social network analysis. Most prior works mainly focus on predicting the total influence spread, i.e., the expected number of influenced nodes given an initial set of active nodes (aka. seeds). However, accurate estimation of susceptibility, i.e., the probability of being influenced for each individual, is more appealing and valuable in real-world applications. Previous methods generally adopt Monte Carlo simulation or heuristic rules to estimate the influence, resulting in high computational cost or unsatisfactory estimation error when these methods are used to estimate susceptibility. In this work, we propose to leverage graph neural networks (GNNs) for predicting susceptibility. As GNNs aggregate multi-hop neighbor information and could generate over-smoothed representations, the prediction quality for susceptibility is undesirable. To address the shortcomings of GNNs for susceptibility estimation, we propose a novel DeepIS model with a two-step approach: (1) a coarse-grained step where we estimate each node's susceptibility coarsely; (2) a fine-grained step where we aggregate neighbors' coarse-grained susceptibility estimations to compute the fine-grained estimate for each node. The two modules are trained in an end-to-end manner. We conduct extensive experiments and show that on average DeepIS achieves five times smaller estimation error than state-of-the-art GNN approaches and two magnitudes faster than Monte Carlo simulation.

本文言語English
ホスト出版物のタイトルWSDM 2021 - Proceedings of the 14th ACM International Conference on Web Search and Data Mining
出版社Association for Computing Machinery, Inc
ページ761-769
ページ数9
ISBN(電子版)9781450382977
DOI
出版ステータスPublished - 2021 8月 3
外部発表はい
イベント14th ACM International Conference on Web Search and Data Mining, WSDM 2021 - Virtual, Online, Israel
継続期間: 2021 3月 82021 3月 12

出版物シリーズ

名前WSDM 2021 - Proceedings of the 14th ACM International Conference on Web Search and Data Mining

Conference

Conference14th ACM International Conference on Web Search and Data Mining, WSDM 2021
国/地域Israel
CityVirtual, Online
Period21/3/821/3/12

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • ソフトウェア

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