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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 04

Published on: April 2026

AI-BASED AUTOMATED SOCIAL MEDIA POSTING SYSTEM

Shruthi Lodi Srinithya Murupoju Shiva Sai Krishna Vardol Nikhil Chowdary Bandi

Hari krishna Mallu

Department of CSE (Data Science) ACE Engineering College  Hyderabad Telangana India

 

Article Status

Plagiarism Passed Peer Reviewed Open Access

Available Documents

Abstract

The AI-Based Automated Social Media Posting System is a software program intended to facilitate the generation of social media posts. In today’s world, having a strong presence on social media is vital, although it involves a great deal of work and commitment. This system employs artificial intelligence technology to generate the caption, hashtags, and even the actual content of social media posts.

The system is capable of identifying the kind of content that would be suitable for individual users by examining the users’ preferences and past performance. Also, the system can identify the most favorable times for posting posts for the benefit of its users. The system combines several APIs to allow for management of social media accounts from various websites like Instagram, Facebook, and Twitter from a single interface.

The software is built using Python and machine learning technologies. The software provides an intuitive user interface that facilitates interaction with the application. The software ensures consistency in the posts and enhances content quality and engagement rates. Overall, the software is a very powerful tool for managing social media accounts.

How to Cite this Paper

Lodi, S., Murupoju, S., Vardol, S. S. K. & Bandi, N. C. (2026). AI-Based Automated Social Media Posting System. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.148

Lodi, Shruthi, et al.. "AI-Based Automated Social Media Posting System." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.148.

Lodi, Shruthi,Srinithya Murupoju,Shiva Vardol, and Nikhil Bandi. "AI-Based Automated Social Media Posting System." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.148.

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References

[1] Discussion on the development of AI-powered social media content generator & poster project, personal communication, 2026.

[2] Ayrshare Social Post API for Python, documentation, https://github.com/ayrshare/social-post-api-python

[3] SakethSripada/Flask-SocialMedia-Automation, code repository, GitHub, https://github.com/SakethSripada/Flask-SocialMedia-Automation, 2024.

[4] SocialBee - AI post generator and social media scheduler, https://socialbee.com/ai-post-generator/, 2025.

[5] Sprout Social - Social media schedulers and management tools, https://sproutsocial.com/insights/social-media-scheduling-tools/, 2025.

[6] Flask Web Application Hardware Requirements, discussion on Reddit - r/flask, 2024.

[7] Create a Flask API for transcribing audio files using Whisper AI, tutorial on Hetzner Community, 2025.

[8] OpenAI API integration using Python Flask, community discussion, 2022

Ethical Compliance & Review Process

  • All submissions are screened under plagiarism detection.
  • Review follows editorial policy.
  • Authors retain copyright.
  • Peer Review Type: Double-Blind Peer Review
  • Published on: Apr 10 2026
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This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

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