Planes of thought dataset: A new dataset for the measurement of human thought by artificial intelligence model based on Cloninger's theory
Today, we have seen remarkable progress in artificial intelligence, especially in natural language processing, chatbots, and sentiment analysis. Using sentiment analysis techniques, chatbots can better understand what users say and produce more useful answers. The more the chatbot understands what the users say, the more interactions between the machine and human will be created. To this end, we must be able to define beyond sentiment analysis for artificial intelligence systems. For this, models must be able to describe and measurement of thought. To solve this challenge, we have created a dataset using Cloninger's theory. In this theory, Cloninger created a global model of human thought and its development, considering the evolution of animal learning abilities to measure thought. Since the thought of humans has not been measured before and accurate measurement is required to perform scientific work, our goal in providing this dataset is to enable artificial intelligence models to do this. Cloninger has divided human thought into five different planes. These planes include: sexual (2), material (3), emotional (4), intellectual (5), and spiritual (7). Three experts labeled the first 10,000 frequently used dictionary words to collect this dataset using Cloninger's theory. We then used these labeled words as ground truths to label sentences. In this dataset, we have labeled 20,000 sentences using this theory so that we can use this dataset to make artificial intelligence models more understanding of the user's statements.
Authors
- Alireza Farnam (ORCID: https://orcid.org/0000-0002-6985-6961)
- Leyli Mohammad Khanli (ORCID: https://orcid.org/0000-0001-7394-5054)
- Yashar Sarbaz (ORCID: https://orcid.org/0000-0002-6258-9653)
- Jafar Tanha (ORCID: https://orcid.org/0000-0002-0779-6027)
- Atra Joudaki
Institutions
- Tabriz University of Medical Sciences (IR)
- University of Tabriz (IR)
Publication Details
- Journal
- Data in Brief
- Published
- 2025-09-04
- DOI
- https://doi.org/10.1016/j.dib.2025.112028
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00