Social Influence Prediction by a Community-Based Convolutional Neural Network

Shao Hsuan Tai, Hao Shang Ma, Jen Wei Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This is an extension from a selected paper from JSAI2019. Learning social influence between users on social networks has beextensively studied in a decade. Many models were proposed to model the microscopic diffusion process or to directly predict the final diffusion results. However, most of them need expensive Monte Carlo simulations to estimate diffusion results and some of them just predict the size of the spread via regression techniques, where people who will adopt the information becomes unknown. In this work, we regard the prediction of final influence diffusion results in a social network as a classification problem to avoid expensive simulations with knowing the final adopters. Furthermore, we propose a community-based convolutional neural network to capture the information of local structure with the aforementioned network. The proposed model is referred to as the Social Influence Learning on Community-based Convolutional Neural Network, SIL-CCNN. In the experiment, SIL-CCNN shows the promising results in both synthetic and real-world datasets. In addition, modeling local structure is indeed useful for the prediction of information diffusion.

Original languageEnglish
Title of host publicationAdvances in Artificial Intelligence - Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence JSAI 2019
EditorsYukio Ohsawa, Katsutoshi Yada, Takayuki Ito, Yasufumi Takama, Eri Sato-Shimokawara, Akinori Abe, Junichiro Mori, Naohiro Matsumura
PublisherSpringer
Pages203-214
Number of pages12
ISBN (Print)9783030398774
DOIs
Publication statusPublished - 2020 Jan 1
Event33rd Annual Conference of the Japanese Society for Artificial Intelligence, JSAI 2019 - Niigata, Japan
Duration: 2019 Jun 42019 Jun 7

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1128 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference33rd Annual Conference of the Japanese Society for Artificial Intelligence, JSAI 2019
CountryJapan
CityNiigata
Period19-06-0419-06-07

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Social Influence Prediction by a Community-Based Convolutional Neural Network'. Together they form a unique fingerprint.

  • Cite this

    Tai, S. H., Ma, H. S., & Huang, J. W. (2020). Social Influence Prediction by a Community-Based Convolutional Neural Network. In Y. Ohsawa, K. Yada, T. Ito, Y. Takama, E. Sato-Shimokawara, A. Abe, J. Mori, & N. Matsumura (Eds.), Advances in Artificial Intelligence - Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence JSAI 2019 (pp. 203-214). (Advances in Intelligent Systems and Computing; Vol. 1128 AISC). Springer. https://doi.org/10.1007/978-3-030-39878-1_19