HEMOS: A novel deep learning-based fine-grained humor detecting method for sentiment analysis of social media

作者：

Highlights：

• We collected 576 frequent Chinese Internet slang expressions as a Chinese slang lexicon.

• We converted the 109 Weibo emojis into textual features creating Chinese emoji lexicon.

• We empirically confirmed inherent humor characteristic to Chinese culture visible on Weibo and divided Weibo posts into four categories.

• We proposed HEMOS, a fine-grained humor detecting method for sentiment analysis of social media.

摘要

•We collected 576 frequent Chinese Internet slang expressions as a Chinese slang lexicon.•We converted the 109 Weibo emojis into textual features creating Chinese emoji lexicon.•We empirically confirmed inherent humor characteristic to Chinese culture visible on Weibo and divided Weibo posts into four categories.•We proposed HEMOS, a fine-grained humor detecting method for sentiment analysis of social media.

论文关键词：Sentiment analysis,Humor polarity,Social media,Emoji,Deep learning

论文评审过程：Received 9 January 2020, Revised 28 April 2020, Accepted 3 May 2020, Available online 20 June 2020, Version of Record 20 June 2020.

论文官网地址：https://doi.org/10.1016/j.ipm.2020.102290