DCAT: a Deep Context-Aware Trust Prediction approach for Online Social Networks

Seyed Mohssen Ghafari, Aditya Joshi, Amin Beheshti, Cecile Paris, Shahpar Yakhchi, Mehmet Orgun

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

7 Citations (Scopus)

Abstract

Customer reviews are now increasingly available on Online Social Networks (OSNs) for a wide range of products and services. Trust in the review's author is a crucial basis for believing in the reliability of reviews generated on such networks. In this context, the main challenge is to predict the unknown trust relationship between two users. Existing trust prediction approaches fail to incorporate textual footprint of users. To address this challenge, we present a deep learning-based graph analytics model to predict trust relations in OSNs. We leverage and extend GraphSAGE, a method for computing node representations in an inductive manner, to develop a deep classifier. We present our experiment with datasets from review websites to train classifiers that predict trust relations between pairs of users, and highlight how our approach significantly improves the quality of predicted trust relations compared to the state-of-the-art approaches.
Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Advances in Mobile Computing & Multimedia (MoMM2019)
EditorsPari Delir Haghighi, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Anderst-Kotsis
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Pages20-27
Number of pages8
ISBN (Electronic)9781450371780
DOIs
Publication statusPublished - 2019
EventInternational Conference on Advances in Mobile Computing & Multimedia (17th : 2019) - Munich, Germany
Duration: 2 Dec 20194 Dec 2019

Publication series

NameACM International Conference Proceeding Series

Conference

ConferenceInternational Conference on Advances in Mobile Computing & Multimedia (17th : 2019)
Abbreviated titleMoMM2019
Country/TerritoryGermany
CityMunich
Period2/12/194/12/19

Keywords

  • Trust Prediction
  • Context-Aware
  • Online Social Networks
  • User Embeddings
  • Deep Learning
  • Graph Convolutional Networks

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