LogosLink User's Manual · LogosLink version 2.0.0

Semantic/Lexical Collocation Analytics (Argumentation Model)

Semantic/Lexical Collocation analytics shows what words appear close to a selected concept in the argumentation model text content.

This is useful to find out major concept/word associations.

Parameters

Focus concept. This is the concept that you want to find across the argumentation model, and for which nearby words are to be determined.
Max distance. This is the maximum number of words before of after an occurrence of the focus concept that will be considered to determine collocated words. Typical values are around 5.
Cross over sentence boundaries. If you check this box, the search for collocated words will cross over sentence boundaries. This will result in more results, but probably less significant, as they will include words that appear in another sentence as compared to the focus concept occurrence.
Include numbers. If you check this box, number words (such as "17" or "-0.25") are also included in the results.
Include codes. If you check this box, code words (such as "UNESCO" or "SARS-CoV-2") are also included in the results.
Case sensitive. If you check this box, words that differ only in case (such as "word" and "Word") are treated as different words.

Results

Results are given as some overall data and a chart.

Overall data

Focus concept occurrence count. This is the number of times that the focus concept occurs in the text.
Collocation count. This is the number of word occurrences that were found within the maximum distance of focus concept occurrences.

Chart

The chart shows the collocated words along the vertical axis. The horizontal axis shows the distance of each collocated word to the focus concept. Blue bars show distance ranges, from minimum to maximum distance. Red circles show average distances, and their size is proportional to the number of occurrences of the collocated word.

You can select how collocated words are sorted from the drop down menu in the toolbar.

Details

Occurrences of the focus concept are found in the text via denotations to the embedded ontology. The analytics looks for denotations of the focus concept, and then searches for collocated words within the maximum distance from each focus concept occurrence, and presents them as results.