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Year 2021, Volume: 6 Issue: 1, 1 - 7, 04.01.2021

Abstract

References

  • Ekman, S. (2012). Data Science Insights. Retrieved from https://www.paulekman.com/
  • Iris, B. (2014, Aug 12). Pleasure, Arousal, Dominance and Russell revisited. Retrieved from http://link.springer.com/article/10.1007/s12144-014-9219-4
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  • Wang, L. (2003). Recent developments in human motion analysis. Pattern Recognition, 36(3), 585–601
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Data Science and Human Behaviour Interpretation and Transformation

Year 2021, Volume: 6 Issue: 1, 1 - 7, 04.01.2021

Abstract

The purpose of this paper is to analyze various dimensions for measurement of human behavior. Human behaviour is complex. Behaviors, emotions, cognitions, and attitudes can rarely be described in terms of one or two variables. It is multimodal in nature. Furthermore, the traits, modalities and dimensions cannot be measured directly, but must be inferred from constructs which in turn are measured by multiple factors or variables. I have emphasized on the use of baseline data for each
subject as the degree of expressiveness for same situation which varies for each subject and needs to be measured based on the individual trait of the subject. This can be done by making baseline data for subjects being researched. Subsequently, discussion has been done on data analysis. Finally, framework for the same has been proposed. Basically, the researcher asks two questions, “Do I have anything important?” (Which is based upon the researcher’s observations of some aspect of human behavior adequately addresses the observation) “If so, what do I have?” (What is the best explanation of the relationship between the variables?)

References

  • Ekman, S. (2012). Data Science Insights. Retrieved from https://www.paulekman.com/
  • Iris, B. (2014, Aug 12). Pleasure, Arousal, Dominance and Russell revisited. Retrieved from http://link.springer.com/article/10.1007/s12144-014-9219-4
  • Fogg, R. (2010). Human Behavior Interpretation, Retrieved from https://www.BehaviorGrid.org
  • Moeslund, T. (2016, Feb 22). A survey of advances in vision-based human motion capture and analysis. Computer Vision and Image Understanding, 104(2-3), 90–126.
  • Sebe, N. (2012). Communication and automatic interpretation of affect from facial expressions. Affective computing and interaction: psychological, cognitive, and neuroscientific perspectives, 8(2), 114-115
  • Vinciarelli, J. (2014). Social signal processing: Survey of an emerging domain. Image and Vision Computing, 27(12), 1743–1759.
  • Wang, L. (2003). Recent developments in human motion analysis. Pattern Recognition, 36(3), 585–601
  • Zeng, Z. (2009). A survey of affect recognition methods: Audio, visual, and spontaneous expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(1), 39–58
There are 8 citations in total.

Details

Primary Language English
Subjects Computer Software
Journal Section Research Article
Authors

Ajit Singh This is me 0000-0002-6093-3457

Publication Date January 4, 2021
Submission Date April 21, 2020
Published in Issue Year 2021 Volume: 6 Issue: 1

Cite

APA Singh, A. (2021). Data Science and Human Behaviour Interpretation and Transformation. Journal of Learning and Teaching in Digital Age, 6(1), 1-7.

Journal of Learning and Teaching in Digital Age 2023. © 2023. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. 19195

Journal of Learning and Teaching in Digital Age. All rights reserved, 2023. ISSN:2458-8350