Force-directed algorithms are a class of methods widely used to solve problems modeled via physics laws and resolved by particle simulation. Visualization of general graphs is one of the research fields which uses such algorithms and provides a vast knowledge about their benefits and challenges. Taking advantage of the knowledge provided by graph visualization theory, some authors have adopted force-directed algorithms as a tool to deal with the community detection problem. However, researches in that direction seem to be neglected by the literature of complex network. This paper explores the use of force-directed algorithms as a tool to solve the community detection problem. We revisit the works proposed in this area and point out the similarities, but mainly highlight the particularities of such a problem concerning the draw of a general graph. This literature review aims to organize the knowledge about the subject and highlight the state-of-the-art. To conduct our review, we followed a research protocol inspired by systematic review guidelines. Our review exposes that many works have chosen models that are not ideal for dealing with the community detection problem. Furthermore, we also highlight the most appropriate force-directed models for community detection.

力导向算法是一类广泛用于解决通过物理定律建模并通过粒子模拟解决的问题的方法。一般图形的可视化是使用此类算法并提供有关其优点和挑战的大量知识的研究领域之一。利用图可视化理论提供的知识，一些作者采用力导向算法作为处理社区检测问题的工具。然而，复杂网络的文献似乎忽略了这方面的研究。本文探讨了使用力导向算法作为解决社区检测问题的工具。我们重新审视了该领域提出的工作并指出了相似之处，但主要强调了有关绘制一般图形的问题的特殊性。这篇文献综述旨在组织有关该主题的知识并突出最新技术。为了进行我们的审查，我们遵循了受系统审查指南启发的研究方案。我们的评论揭示了许多工作选择的模型对于处理社区检测问题并不理想。此外，我们还强调了最适合社区检测的力导向模型。