Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs
Moral elevation, the emotion that arises when individuals observe others’ moral behaviors, plays an important role in determining moral behaviors in real life. While recent research has demonstrated the potential to decode basic emotions with brain signals, there has been limited exploration of affe...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2023-01-01
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| Series: | Cyborg and Bionic Systems |
| Online Access: | https://spj.science.org/doi/10.34133/cbsystems.0028 |
| _version_ | 1797798222196899840 |
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| author | Chenhao Bao Xin Hu Dan Zhang Zhao Lv Jingjing Chen |
| author_facet | Chenhao Bao Xin Hu Dan Zhang Zhao Lv Jingjing Chen |
| author_sort | Chenhao Bao |
| collection | DOAJ |
| description | Moral elevation, the emotion that arises when individuals observe others’ moral behaviors, plays an important role in determining moral behaviors in real life. While recent research has demonstrated the potential to decode basic emotions with brain signals, there has been limited exploration of affective computing for moral elevation, an emotion related to social cognition. To address this gap, we recorded electroencephalography (EEG) signals from 23 participants while they viewed videos that were expected to elicit moral elevation. More than 30,000 danmaku comments were extracted as a crowdsourcing tagging method to label moral elevation continuously at a 1-s temporal resolution. Then, by employing power spectra features and the least absolute shrinkage and selection operator regularized regression analyses, we achieved a promising prediction performance for moral elevation (prediction r = 0.44 ± 0.11). Our findings indicate that it is possible to decode moral elevation using EEG signals. Moreover, the small-sample neural data can predict the continuous moral elevation experience conveyed in danmaku comments from a large population. |
| first_indexed | 2024-03-13T04:00:15Z |
| format | Article |
| id | doaj.art-a9f9b86364cf4295aa7762d59f22ce02 |
| institution | Directory Open Access Journal |
| issn | 2692-7632 |
| language | English |
| last_indexed | 2024-03-13T04:00:15Z |
| publishDate | 2023-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Cyborg and Bionic Systems |
| spelling | doaj.art-a9f9b86364cf4295aa7762d59f22ce022023-06-21T15:39:37ZengAmerican Association for the Advancement of Science (AAAS)Cyborg and Bionic Systems2692-76322023-01-01410.34133/cbsystems.0028Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGsChenhao Bao0Xin Hu1Dan Zhang2Zhao Lv3Jingjing Chen4Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.Department of Psychology, School of Social Sciences, Tsinghua University, Beijing 100084, China.School of Computer Science and Technology, Anhui University, Hefei 230601, China.Department of Psychology, School of Social Sciences, Tsinghua University, Beijing 100084, China.Moral elevation, the emotion that arises when individuals observe others’ moral behaviors, plays an important role in determining moral behaviors in real life. While recent research has demonstrated the potential to decode basic emotions with brain signals, there has been limited exploration of affective computing for moral elevation, an emotion related to social cognition. To address this gap, we recorded electroencephalography (EEG) signals from 23 participants while they viewed videos that were expected to elicit moral elevation. More than 30,000 danmaku comments were extracted as a crowdsourcing tagging method to label moral elevation continuously at a 1-s temporal resolution. Then, by employing power spectra features and the least absolute shrinkage and selection operator regularized regression analyses, we achieved a promising prediction performance for moral elevation (prediction r = 0.44 ± 0.11). Our findings indicate that it is possible to decode moral elevation using EEG signals. Moreover, the small-sample neural data can predict the continuous moral elevation experience conveyed in danmaku comments from a large population.https://spj.science.org/doi/10.34133/cbsystems.0028 |
| spellingShingle | Chenhao Bao Xin Hu Dan Zhang Zhao Lv Jingjing Chen Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs Cyborg and Bionic Systems |
| title | Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs |
| title_full | Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs |
| title_fullStr | Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs |
| title_full_unstemmed | Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs |
| title_short | Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs |
| title_sort | predicting moral elevation conveyed in danmaku comments using eegs |
| url | https://spj.science.org/doi/10.34133/cbsystems.0028 |
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