Neurological Prediction of digital growth metrics using Artificial Intelligence: Social Media Automation

Authors

  • Tanvi, Inderpal Singh, Anshu Sharma, Chirag Sharma, Rachit Garg

DOI:

https://doi.org/10.47750/pnr.2022.13.S08.526

Abstract

This research aims to use artificial intelligence to provide technical insights, neurological insights and assistance and ease the work of professional content creators. It also discusses benefits and processes to predict potential metrics for any social media handle using the account’s data and AI-enabled algorithm. The discussed research questions are implemented using a proposed methodology and then results are discussed, including approximately 91% accurately predicted hashtags, 0.7 R2 scores and approximately 78% acceptance rate by various influencers for the generated post content. For these results, I worked with 10 influencers of every level small to medium who was ready to work on this system privately because data can’t be shared publicly.

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Published

2023-01-03 — Updated on 2023-01-04

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How to Cite

Neurological Prediction of digital growth metrics using Artificial Intelligence: Social Media Automation. (2023). Journal of Pharmaceutical Negative Results, 4172-4176. https://doi.org/10.47750/pnr.2022.13.S08.526 (Original work published 2023)