Word embeddings represent a significant advancement in the field of natural language processing. Traditionally, a neural network is employed to organize words within a hyperdimensional space. However, alternative approaches, such as the use of a spring-force system, may offer a promising alternative. This paper presents the initial concept of such an approach and the findings of a preliminary experiment that yielded encouraging results.