Data Science and Human Behaviour Interpretation and Transformation

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?)

Keywords

• Human Behavior Analysis
• Data Science
• ABC model of attitude
• Framework
• XML

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