Summary of Surveying the Dead Minds: Historical-psychological Text Analysis with Contextualized Construct Representation (ccr) For Classical Chinese, by Yuqi Chen et al.
Surveying the Dead Minds: Historical-Psychological Text Analysis with Contextualized Construct Representation (CCR) for Classical Chinese
by Yuqi Chen, Sixuan Li, Ying Li, Mohammad Atari
First submitted to arxiv on: 1 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty summary: This paper presents a novel pipeline for analyzing historical texts in classical Chinese, specifically targeting psychological constructs such as traditionalism, norm strength, and collectivism. The Contextualized Construct Representations (CCR) approach combines expert knowledge in psychometrics with transformer-based language models to measure these psychological constructs. To address the scarcity of available data, an indirect supervised contrastive learning approach is proposed, along with the construction of the Chinese historical psychology corpus (C-HI-PSY). Experimental results demonstrate the superior performance of the CCR method compared to word-embedding-based approaches and prompting with GPT-4 in most tasks. The pipeline’s validity is further verified through benchmarking against objective, external data. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty summary: This paper helps computers understand old Chinese texts that talk about people’s thoughts and feelings thousands of years ago. Most computer programs focus on modern languages, but this one tries to figure out what ancient cultures were thinking by combining human expertise with special language models. They built a special collection of old Chinese texts and used it to test their method. It worked better than other ways they tried! This could help us learn more about the past. |
Keywords
» Artificial intelligence » Embedding » Gpt » Prompting » Supervised » Transformer
