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Research Article | Open Access |

Optimizing Social Media Marketing Strategies Through Sentiment Analysis and Firefly Algorithm Techniques

Author 1: Sudhir Anakal Author 2: P N S Lakshmi Author 3: Nishant Fofaria Author 4: Janjhyam Venkata Naga Ramesh Author 5: Elangovan Muniyandy Author 6: Shaik Sanjeera Author 7: Yousef A.Baker El-Ebiary Author 8: Ritesh Patel
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 16, No. 2 · Published 2025 · Cited by 5

DOI: https://doi.org/10.14569/IJACSA.2025.01602112

Abstract

The dramatic expansion of social media platforms reshaped business-to-customer interactions so organizations need to refine their marketing strategies toward maximizing both user engagement and marketing return on investment (ROI). Present-day social media marketing methods struggle to embrace user emotions fully while responding to market variations thus demonstrating the necessity for developing innovative social media marketing tools. Studies seek to boost social media marketing performance through an FA integration with sentiment analysis for content strategy optimization and better user engagement results. This study adopts novel techniques by combining sentiment analysis with the Firefly Algorithm to optimize marketing strategies in real-time and it represents an underutilized approach in present research. Eventually combined fields generate a sentiment-driven and data-oriented decision-making capability in social media marketing applications. The proposed system combines sentiment analysis technology that measures social media emotion levels alongside the Firefly Algorithm which applies optimization methods to marketing tactics based on present feedback. The framework operates through dynamic adjustments of content strategies which maximize user engagement. The proposed method demonstrated 98.4% precision in forecasting user engagement metrics and adapting content strategies. Results show traditional marketing strategies yield to these approaches by improving user interaction alongside campaign effectiveness. The research introduces a new optimization method in social media marketing which integrates sentiment analysis with Firefly Algorithm technology. Research findings suggest this combined methodology brings substantial precision improvements to marketing strategies by offering companies an effective method to optimize digital marketplace outcomes.

Keywords

How to Cite this Article

Anakal, S., Lakshmi, P. N. S., Fofaria, N., Ramesh, J. V. N., Muniyandy, E., Sanjeera, S., El-Ebiary, Y. A., & Patel, R. (2025). Optimizing Social Media Marketing Strategies Through Sentiment Analysis and Firefly Algorithm Techniques. International Journal of Advanced Computer Science and Applications, 16(2). https://doi.org/10.14569/IJACSA.2025.01602112

Anakal, Sudhir, et al.. "Optimizing Social Media Marketing Strategies Through Sentiment Analysis and Firefly Algorithm Techniques." International Journal of Advanced Computer Science and Applications, vol. 16, no. 2, 2025, https://doi.org/10.14569/IJACSA.2025.01602112.

@article{Anakal2025,
  title     = {Optimizing Social Media Marketing Strategies Through Sentiment Analysis and Firefly Algorithm Techniques},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {2},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Sudhir Anakal and P N S Lakshmi and Nishant Fofaria and Janjhyam Venkata Naga Ramesh and Elangovan Muniyandy and Shaik Sanjeera and Yousef A.Baker El-Ebiary and Ritesh Patel},
  doi       = {10.14569/IJACSA.2025.01602112},
  url       = {https://doi.org/10.14569/IJACSA.2025.01602112}
}

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