Papers by John Priniski
Pipeline for modeling causal beliefs from natural language (2023.acl-demo)
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| Challenge: | Existing methods to analyze language data for psychological causality are difficult to advance as they do not isolate cognitive mechanisms. |
| Approach: | They propose a pipeline that leverages a Large Language Model to identify causal claims made in natural language documents and applies a clustering algorithm to group causal claims based on their semantic topics. |
| Outcome: | The proposed pipeline analyzes the Covid-19 vaccine in tweets and generates a causal claim network. |