Detecting clickbaits using two-phase hybrid CNN-LSTM biterm model

作者：

Highlights：

• A ground dataset has been prepared from Facebook page and Reddit website.

• Extraction of text from non-textual (image-based) data using pre-processing approach.

• Automatic identification of the eight types of clickbait is done.

• A novel approach is proposed which works under two-phase structure.

• Shocking/Unbelievable, Hypothesis/Guess, Reaction types of clickbait are published maximum on social media.

摘要

•A ground dataset has been prepared from Facebook page and Reddit website.•Extraction of text from non-textual (image-based) data using pre-processing approach.•Automatic identification of the eight types of clickbait is done.•A novel approach is proposed which works under two-phase structure.•Shocking/Unbelievable, Hypothesis/Guess, Reaction types of clickbait are published maximum on social media.

论文关键词：Clickbait,News,Classifier,Features,Social media

论文评审过程：Received 27 August 2019, Revised 27 February 2020, Accepted 27 February 2020, Available online 28 February 2020, Version of Record 8 March 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113350