  There are increasingly applications of natural language processing techniques
for information retrieval, indexing and topic modelling in the engineering
contexts. A standard component of such tasks is the removal of stopwords, which
are uninformative components of the data. While researchers use readily
available stopword lists which are derived for general English language, the
technical jargon of engineering fields contains their own highly frequent and
uninformative words and there exists no standard stopword list for technical
language processing applications. Here we address this gap by rigorously
identifying generic, insignificant, uninformative stopwords in engineering
texts beyond the stopwords in general texts, based on the synthesis of
alternative data-driven approaches, and curating a stopword list ready for
technical language processing applications.
