Natural language processing research has been on the increase since the first evidence of research in the area was published in 1958. This paper examined the document types, source types, source titles, affiliations, open access type, funders, countries of affiliation of researchers, volume and growth of literature 1958–2021, growth of NLP literature (1958–2021), and visualized and mapped all keywords on the area as indexed in Scopus during the period. Basic bibliometric indicators, including all keywords, were collected on February 22, 2022. Articles (85.96) were the most prominent document types, while Ceur Workshop Proceedings were the most source type. Chinese Academy of Science was the affiliation of the highest number of authors on the subject, Green open access documents (53.56%) and undefined funders provided funding for research in the area the most and the Chinese national address (14.66%) had the highest frequency. The linear forecast shows that research in the area continues to attract the attention of researchers. Keywords have grown in number and scope of linguistics and computer science issues that dominate research in the area while Natural Language Processing is the most dominant keyword in the area. NLP is a computer science subject, and attention to the subject has attracted the interest of researchers from various disciplines.