Home / Current Issue / Paper 1711882
AI social media manager
Subject area: Science,Engineering and Technology · Area of research: Gen AI in Social media marketing
DOI: https://doi.org/10.64388/IREV9I5-1711882
Abstract
The management of social media for brands and individuals is a critical but highly inefficient process. Professionals rely on a fragmented suite of tools for content creation, scheduling, and performance analysis , a disconnection that hinders the ability to translate analytical data into effective content strategy. This paper introduces the AI-Powered Social Media Manager, a unified platform designed to solve these challenges. The system's core contribution is a novel, stateful agentic workflow built with langgraph, which dynamically manages the entire content lifecycle. This architecture integrates a generative AI for image and text creation , an automated scheduling engine powered by apscheduler , and a comprehensive analytics dashboard. By creating an integrated feedback loop, the system analyzes post engagement and current trends to provide data-driven strategic recommendations for future content. Results demonstrate that this unified system significantly streamlines the management workflow, reducing the time-to-post from over 8 minutes to under 3. The successful implementation of this proof-of-concept demonstrates that unifying these core functions through an agentic AI represents a notable improvement over traditional, multi-platform management methods.
Keywords
Social Media Management, Generative AI, Agentic Workflow, LangGraph, Workflow Automation, Social Media Analytics, Content Strategy.
How to cite this paper
@article{1711882,
author = {Utkarsh Barbhai, Soham Dhapate, Harshad Potdar, Sarvesh Mohite},
title = {AI social media manager},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {523-530},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1711882.pdf},
abstract = {The management of social media for brands and individuals is a critical but highly inefficient process. Professionals rely on a fragmented suite of tools for content creation, scheduling, and performance analysis , a disconnection that hinders the ability to translate analytical data into effective content strategy. This paper introduces the AI-Powered Social Media Manager, a unified platform designed to solve these challenges. The system's core contribution is a novel, stateful agentic workflow built with langgraph, which dynamically manages the entire content lifecycle. This architecture integrates a generative AI for image and text creation , an automated scheduling engine powered by apscheduler , and a comprehensive analytics dashboard. By creating an integrated feedback loop, the system analyzes post engagement and current trends to provide data-driven strategic recommendations for future content. Results demonstrate that this unified system significantly streamlines the management workflow, reducing the time-to-post from over 8 minutes to under 3. The successful implementation of this proof-of-concept demonstrates that unifying these core functions through an agentic AI represents a notable improvement over traditional, multi-platform management methods.},
keywords = {Social Media Management, Generative AI, Agentic Workflow, LangGraph, Workflow Automation, Social Media Analytics, Content Strategy.},
month = {November},
doi = {https://doi.org/10.64388/IREV9I5-1711882}
}