Supervised group embedding for rumor detection in social media

Yuwei Liu, Xingming Chen, Yanghui Rao, Haoran Xie, Qing Li, Jun Zhang, Yingchao Zhao, Fu Lee Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)


To detect rumors automatically in social media, methods based on recurrent neural network and convolutional neural network have been proposed. These methods split a stream of posts related to an event into several groups along time, and represent each group using unsupervised methods such as paragraph vector. However, many posts in a group (e.g., retweeted posts) do not contribute much to rumor detection, which deteriorates the performance of rumor detection based on unsupervised group embedding. In this paper, we propose a Supervised Group Embedding based Rumor Detection (SGERD) model that considers both textual and temporal information. Particularly, SGERD exploits post-level textual information to generate group embeddings, and is able to identify salient posts for further analysis. Experimental results on two real-world datasets demonstrate the effectiveness of our proposed model.

Original languageEnglish
Title of host publicationWeb Engineering - 19th International Conference, ICWE 2019, Proceedings
EditorsMaxim Bakaev, Flavius Frasincar, In-Young Ko
Number of pages15
ISBN (Print)9783030192730
Publication statusPublished - 1 Jan 2019
Event19th International Conference on Web Engineering, ICWE 2019 - Daejeon, Korea, Republic of
Duration: 11 Jun 201914 Jun 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11496 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th International Conference on Web Engineering, ICWE 2019
Country/TerritoryKorea, Republic of


  • Convolutional Neural Network
  • Rumor detection
  • Social media

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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