We have published and presented this paper at the International Conference on Enterprise Information Systems (ICEIS 2024). DOI: https://doi.org/10.5220/0012615100003690
ABSTRACT:
Social network sites serve as effective platforms for word-of-mouth marketing (WOM), often analyzed through Agent-Based Models (ABMs). However, implementing ABMs can be daunting, with programmers facing
the choice of building from scratch or using frameworks. To tackle this, we propose FASOW (Flexible Agent Simulator for Open WOM) architecture, employing the Reflective Tower design. FASOW’s four layers cater to varying complexities, simplifying implementation by breaking down models into manageable sub-layers. We validate FASOW through a case study on Twitter, examining agent saturation effects in WOM marketing. Results indicate FASOW’s efficacy, though further use cases are needed for comprehensive evaluation. Additionally, we offer an online proof-of-concept for this architecture.