Name
Abstract | ||
|---|---|---|
In this paper, we show how game-theoretic work on conversation combined with a theory of discourse structure provides a framework for studying interpretive bias. Interpretive bias is an essential feature of learning and understanding but also something that can be used to pervert or subvert the truth. The framework we develop here provides tools for understanding and analyzing the range of interpretive biases and the factors that contribute to them. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Computation and Language | Conversation,Computer science,Cognitive science,Artificial intelligence,Natural language processing,Interpretive bias,Discourse structure |
DocType | Volume | Citations |
Journal | abs/1806.11322 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicholas Asher | 1 | 6 | 3.23 |
| Soumya Paul | 2 | 29 | 5.87 |