Digital Marketing Analysis on Social Media Using Machine Learning

Authors

  • A Mounika Department of Computer Science & Engineering, PACE Institute of Technology and Sciences, Ongole, Andhra Pradesh, India Author
  • T Venkata Naga Jayanth Department of Computer Science & Engineering, PACE Institute of Technology and Sciences, Ongole, Andhra Pradesh, India Author
  • M Venkata Vishnu Vardhan Department of Computer Science & Engineering, PACE Institute of Technology and Sciences, Ongole, Andhra Pradesh, India Author
  • S Sai Venkata BharadwaJ Department of Computer Science & Engineering, PACE Institute of Technology and Sciences, Ongole, Andhra Pradesh, India Author
  • M Shalim Raj Department of Computer Science & Engineering, PACE Institute of Technology and Sciences, Ongole, Andhra Pradesh, India Author
  • I Kiran Kumar Department of Computer Science & Engineering, PACE Institute of Technology and Sciences, Ongole, Andhra Pradesh, India Author

DOI:

https://doi.org/10.55524/ijircst.2023.11.3.20

Keywords:

machine learning, digital marketing, social media, fuzzy set

Abstract

he field of machine learning has received  insufficient attention. Because of their superior Artificial  Intelligence, machines that are capable of deep learning have  the potential to push the boundaries of what is possible in  digital marketing. This study intends to uncover the out 

comes from the study of Indian customers' responses across  a variety of demographics to machines and their capacities to  sell, which may very well be the future of digital marketing.  We have found that software developers need to construct  the architecture in conjunction with digital marketers. These  digital marketers utilize machines with deep learning to take  into consideration the attitudes of customers as well as their  behaviors and choices. As a result, in the not-too-distant  future, marketers will have convenient access to correct  information regarding clients, which will unlock enormous  benefits for the companies. A causal model that makes use  of regression models is used to explain how the performance  of the machines is likely to change depending on the circum stances. SPSS version 24 and R software were used for the  analysis of the data. Data regarding the customer's behaviors,  their choices, and emotions are collected, and fuzzy-set qual itative comparative analysis (fsQCA) approach is used to  determine how they can be influenced to use the services of  the machine. 

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Published

2023-05-30

How to Cite

Digital Marketing Analysis on Social Media Using Machine Learning . (2023). International Journal of Innovative Research in Computer Science & Technology, 11(3), 101–104. https://doi.org/10.55524/ijircst.2023.11.3.20