Yıl 2021, Cilt 6 , Sayı 1, Sayfalar 1 - 7 2021-01-04

Data Science and Human Behaviour Interpretation and Transformation

Ajit SİNGH [1]


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?)
Human Behavior Analysis, Data Science, ABC model of attitude, Framework, XML
  • 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
Birincil Dil en
Konular Bilgisayar Bilimleri, Bilgi Sistemleri
Bölüm Research Article
Yazarlar

Orcid: 0000-0002-6093-3457
Yazar: Ajit SİNGH (Sorumlu Yazar)
Kurum: Patna Women's College, Bihar
Ülke: India


Tarihler

Başvuru Tarihi : 21 Nisan 2020
Kabul Tarihi : 21 Mayıs 2020
Yayımlanma Tarihi : 4 Ocak 2021

APA Singh, A . (2021). Data Science and Human Behaviour Interpretation and Transformation . Journal of Learning and Teaching in Digital Age , 6 (1) , 1-7 . Retrieved from https://dergipark.org.tr/tr/pub/joltida/issue/59433/853784