AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments

October 11, 2024 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

๐Ÿ‘ป CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Till Raphael Saenger, Musashi Hinck, Justin Grimmer, Brandon M. Stewart arXiv ID 2410.08917 Category cs.CL: Computation & Language Citations 4 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 5 months ago
Abstract
We introduce AutoPersuade, a three-part framework for constructing persuasive messages. First, we curate a large dataset of arguments with human evaluations. Next, we develop a novel topic model to identify argument features that influence persuasiveness. Finally, we use this model to predict the effectiveness of new arguments and assess the causal impact of different components to provide explanations. We validate AutoPersuade through an experimental study on arguments for veganism, demonstrating its effectiveness with human studies and out-of-sample predictions.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

๐Ÿ“œ Similar Papers

In the same crypt โ€” Computation & Language

๐ŸŒ… ๐ŸŒ… Old Age

Attention Is All You Need

Ashish Vaswani, Noam Shazeer, ... (+6 more)

cs.CL ๐Ÿ› NeurIPS ๐Ÿ“š 166.0K cites 9 years ago

Died the same way โ€” ๐Ÿ‘ป Ghosted