"In the Great Wargaming Survey, 2025 edition, one survey question asked respondents, "What do you like most about miniatures wargaming?" Responses were collected as unstructured text (up to about 2,100 characters per response and anything goes!) allowing participants to write without constraint to include all of the facets of wargaming that they like. In total, there were 4,063 non-blank responses recorded. I last looked at this question in GWS 2023. I wonder if wargamers' "likes" have changed since then?
To parse and interpret this large body of text, machine learning techniques are introduced. Specifically, a variety of cluster analysis techniques are applied to the survey data. These statistical methods help uncover underlying data associations and reduce thousands of unique words (tokens) to a smaller dataset. The aim of this data reduction step is to transform unstructured text into a manageable set of representative tokens while preserving essential meaning.
After routine preprocessing and tokenization, the dataset produced 2,719 unique terms with associated frequencies. A further data step involved removing near-zero variance terms thereby reducing this set dramatically to just nineteen key word tokens. These nineteen tokens are…"
Palouse Wargaming Journal
link
Armand
