Name
Title | ||
|---|---|---|
HEMOS: A novel deep learning-based fine-grained humor detecting method for sentiment analysis of social media |
Abstract | ||
|---|---|---|
•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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ipm.2020.102290 | Information Processing & Management |
Keywords | DocType | Volume |
Sentiment analysis,Humor polarity,Social media,Emoji,Deep learning | Journal | 57 |
Issue | ISSN | Citations |
6 | 0306-4573 | 1 |
PageRank | References | Authors |
0.36 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Da Li | 1 | 3 | 2.81 |
| Rafal Rzepka | 2 | 187 | 40.62 |
| Michal Ptaszynski | 3 | 132 | 25.47 |
| Kenji Araki | 4 | 343 | 80.17 |