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This research utilised the concept of big data analytics in combination with a deep radial basis function network to make a prediction regarding the behaviour of prospective clients on social media. The manner in which individuals make use of social media has been investigated by researchers using a set of criteria and factors. The research investigated the experiences that clients had with the social networking website. The research takes use of data pre-processing techniques to discover and eliminate outliers, noise, errors, and duplicate records. This is done to guarantee that the results from the research are of a high quality. To anticipate the manner in which users will engage with the social media platform, the researchers developed mathematical models that made use of machine learning. The objective of this model is to generate a prediction on the manner in which users will engage with the social networking site.

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Predictive Modelling of Social Media Behaviour Using Deep Learning: A Big Data Analytics Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Biju Balakrishnan,
  • S. Muthumarilakshmi,
  • Dhinakaran Krishnan,
  • R. Sivakoumar,
  • R. Amudha

摘要

This research utilised the concept of big data analytics in combination with a deep radial basis function network to make a prediction regarding the behaviour of prospective clients on social media. The manner in which individuals make use of social media has been investigated by researchers using a set of criteria and factors. The research investigated the experiences that clients had with the social networking website. The research takes use of data pre-processing techniques to discover and eliminate outliers, noise, errors, and duplicate records. This is done to guarantee that the results from the research are of a high quality. To anticipate the manner in which users will engage with the social media platform, the researchers developed mathematical models that made use of machine learning. The objective of this model is to generate a prediction on the manner in which users will engage with the social networking site.