Digital humanistic knowledge production emphasises the importance of a strong knowledge production community and differentiates from traditional knowledge production models, which include aspects such as online and cooperative knowledge development. The digital humanities knowledge production community model is already widely acknowledged. However, the features and characteristics of digital humanistic knowledge production under natural language processing are controversial. This research presents a wordVEA digital humanistic knowledge production feature mining approach based on a word2vec and variational self-encoder (VAE). The knowledge production characteristics of digital humanistic are primarily defined by the coexistence of a knowledge production structure and boundary blurring, as well as interdisciplinary collaboration thematic cohesiveness and broad horizon, as determined by the research results which effectively address the question of the characteristics of digital humanistic knowledge production through application of the word VAE method.