Fake news detection using an ensemble learning model based on Self-Adaptive Harmony Search algorithms

作者：

Highlights：

• The appropriate features of news are analyzed for training models.

• The ensemble learning model for fake news detection is proposed in the paper.

• The weights of the ensemble learning model are optimized in the paper.

• The cross-domain intractability issue is investigated in the paper.

摘要

•The appropriate features of news are analyzed for training models.•The ensemble learning model for fake news detection is proposed in the paper.•The weights of the ensemble learning model are optimized in the paper.•The cross-domain intractability issue is investigated in the paper.

论文关键词：Deep learning,Fake news,Natural language processing,Harmony search algorithm

论文评审过程：Received 24 December 2019, Revised 17 May 2020, Accepted 17 May 2020, Available online 25 May 2020, Version of Record 3 June 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113584