Natural language processing or NLP is a branch of artificial intelligence that deals with the interaction between computers and human language. The goal of NLP is to give machines the ability to understand, analyze, and generate natural language. Natural language processing is an interdisciplinary science that tries to facilitate the interaction between human language and computer by using computer science, linguistics and artificial intelligence. In this paper, we present a method for producing synthetic digital poetry using word embedding technology. Word embedding is a technique used to represent words as numerical vectors in multidimensional space. This technique allows NLP to better understand the semantic and syntactic connections between words. The importance and advantages of using the word vector are discussed below. Machine learning models using word vectors have higher accuracy in analysis and prediction. These models can learn more complex relationships and patterns. Also, some future gaps are presented to continue this work.