Papers with baseline classifiers
“President Vows to Cut <Taxes> Hair”: Dataset and Analysis of Creative Text Editing for Humorous Headlines (N19-1)
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| Challenge: | Existing datasets address specific humor templates, such as funny one-liners and filling in Mad Libs R. |
| Approach: | They introduce a dataset for research in computational humor that uses crowdsourced editing techniques to create funny headlines. |
| Outcome: | The new dataset supports classic theories of humor, including incongruity, superiority, setup/punchline. |
WikiTalkEdit: A Dataset for modeling Editors’ behaviors on Wikipedia (2021.naacl-main)
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| Challenge: | Using the WikiTalkEdit dataset, we show how positive emotion and the use of first-person pronouns predict a positive emotional change in a Wikipedia contributor. |
| Approach: | They introduce and analyze WikiTalkEdit, a dataset of conversations and edit histories from Wikipedia, for research in online cooperation and conversation modeling. |
| Outcome: | The proposed dataset supports the classic understanding of style matching, where positive emotion and the use of first-person pronouns predict a positive emotional change in a Wikipedia contributor. |