AI Article Synopsis
- Researchers are exploring implicit attitudes toward climate change to better understand public opinion, which is currently unclear.
- They developed a custom Single-Category Implicit Association Test to evaluate these beliefs, using eye tracking technology to monitor the participants' gaze patterns.
- Analysis of the eye-tracking data revealed significant differences in reactions to climate change-related stimuli, indicating that eye-tracking could serve as a valuable alternative to traditional methods like electroencephalography for assessing implicit attitudes.
Article Abstract
Raising awareness of environmental challenges represents an important issue for researchers and scientists. As public opinion remains ambiguous, implicit attitudes toward climate change must be investigated. A custom Single-Category Implicit Association Test, a version of the Implicit Association Test, was developed to assess climate change beliefs. It was administered to 20 subjects while eye movements were tracked using a smart glasses system. Eye gaze patterns were analysed to understand whether they could reflect implicit attitudes toward nature. Recurrence Quantification Analysis was performed to extract 13 features from the eye-tracking data, which were used to perform statistical analyses. Significant differences were found between target stimuli (words related to climate change) and bad attributes in reaction time, and between target stimuli and good attributes in diagonal length entropy, suggesting that eye-tracking may provide an alternative source of information to electroencephalography in modeling and predicting implicit attitudes.
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| http://dx.doi.org/10.1109/EMBC40787.2023.10340147 | DOI Listing |
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