AI-driven computational social networks for sustainable B2B marketing
Abstract
Business-to-business (B2B) marketing is a major driver of global economic growth and competitiveness. In an increasingly dynamic environment, the need for sustainable success and rivalry pushes B2B firms to adopt creative, data-driven strategies. Social media platforms now play a crucial role in nurturing customer relationships and strengthening brand loyalty. This study proposes a long-term B2B marketing strategy that integrates social media with artificial intelligence (AI)-driven Natural Language Processing (NLP) within an AI-based Computational Social Network (AI-CSN) framework. The approach aims to understand customers not only by their preferences but also by their behaviors and habits. Using NLP, the system mines blogs, social media, and customer feedback to extract actionable insights, detect patterns, and support data-driven campaign decisions. Simulation results, based on real B2B marketing data, show improvements in customer engagement and revenue. The system’s effectiveness is evaluated through user interactions, product ratings, and customer reviews, indicating potential for stronger brand.
Author
Nashwan Adnan OTHMAN
ISSN
Publish Date: 19-May-2026