Papers by Johannes Eichstaedt
Discourse-Level Representations can Improve Prediction of Degree of Anxiety (2023.acl-short)
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Swanie Juhng, Matthew Matero, Vasudha Varadarajan, Johannes Eichstaedt, Adithya V Ganesan, H. Andrew Schwartz
| Challenge: | Anxiety disorders are the most common of mental illnesses, but little is known about how to detect them from language. |
| Approach: | They propose to use discourse-level information in addition to lexical-level large language model embeddings to evaluate the utility of a lexico-discourse model. |
| Outcome: | The proposed model outperforms models based on state-of-the-art contextual embeddings and uses discourse patterns of causal explanations significantly more than models derived from Sentence-BERT and DiscRE, and is comparable to psychological models. |