Evidence map›Paper›PMID 38277084›Full record

ArticleBehavior research methods2024

Can generative AI infer thinking style from language? Evaluating the utility of AI as a psychological text analysis tool.

David M Markowitz

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Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

David M MarkowitzDepartment of Communication, Michigan State University, East Lansing, MI, USA. dmm@msu.edu.ORCID http://orcid.org/0000-0002-7159-7014

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Generative AI, short for Generative Artificial Intelligence, a class of artificial intelligence systems, is not currently the choice technology for text analysis, but prior work suggests it may have some utility to assess dynamics like emotion. The current work builds upon this empirical foundation to consider how analytic thinking scores from a large language model chatbot, ChatGPT, were linked to analytic thinking scores from dictionary-based tools like Linguistic Inquiry and Word Count (LIWC). Using over 16,000 texts from four samples and tested against three prompts and two large language models (GPT-3.5, GPT-4), the evidence suggests there were small associations between ChatGPT and LIWC analytic thinking scores (meta-analytic effect sizes: .058 < rs < .304; ps < .001). When given the formula to calculate the LIWC analytic thinking index, ChatGPT performed incorrect mathematical operations in 22% of the cases, suggesting basic word and number processing may be unreliable with large language models. Researchers should be cautious when using AI for text analysis.

Indexed as

Artificial IntelligenceLanguageThinkingHumansAnalytic thinkingGenerative AILarge language modelsLIWCText analysis

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.