Human Behavior Analytics in the Era of Digital Interaction

  • Authors

    • H. N. Mahabala Computer Scientist, Tata Institute of Fundamental Research, India. Author

    DOI:

    https://doi.org/10.67228/3071561X/IJIRHT-2025PI6M4H

    Published 01-04-2025

  • Human Behavior Analytics, Digital Interaction, Artificial Intelligence, Machine Learning, User Behavior Modeling, Predictive Analytics, Digital Transformation, Behavioral Intelligence, Data Analytics, Cybersecurity

    Issue

    Vol. 8 No. 1 (2025)

    Section

    Articles

    How to Cite

    [1]
    M. H. N, “Human Behavior Analytics in the Era of Digital Interaction”, IJIRHT, vol. 8, no. 1, pp. 01–16, Jan. 2025, doi: 10.67228/3071561X/IJIRHT-2025PI6M4H.

  • Abstract

    Human Behavior Analytics (HBA) is an emerging interdisciplinary field that combines data science, artificial intelligence (AI), machine learning (ML), psychology, and behavioral sciences to understand and predict human behavior in digital environments. By analyzing data from social media, e-commerce, mobile applications, and online platforms, HBA helps organizations improve personalization, decision-making, cybersecurity, and user experiences. This study proposes a comprehensive HBA framework incorporating data collection, preprocessing, feature engineering, machine learning models, and decision intelligence. Using simulated digital interaction data, the framework demonstrates improved accuracy in user profiling, engagement prediction, anomaly detection, and decision support. Despite its benefits, HBA raises ethical concerns related to privacy, consent, algorithmic bias, and data security. Therefore, responsible AI practices and regulatory compliance are essential. The findings emphasize HBA’s growing strategic importance in the digital economy and highlight the need for explainable AI, privacy-preserving analytics, and ethical behavioral intelligence systems in future research.

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