Wordnet is a lexical database maintained by Princeton university. It is described as:
“WordNet® is a large lexical database of English, developed under the direction of George A. Miller. Nouns, verbs, adjectives and adverbs are grouped into sets of cognitive synonyms (synsets), each expressing a distinct concept. Synsets are interlinked by means of conceptual-semantic and lexical relations. The resulting network of meaningfully related words and concepts can be navigated with the browser”
When we with to do autocoding with NVivo or other qualitative research (or content analysis) software, wordnet is a good companion. It enables us to make a large set of conceptually related words that we can find and code automatically in our textual data. For example, I wished to identify all passages where the notion of anger is represented in over 200 newspaper articles. It would have made me rather angry to wade through all the 200 documents. Instead, I generated to following set of words using wordnet: Furious, Angry, Rage, Wild, Aggravate, Provoke, Infuriated, Sore, Irate, Irritate, Wrath, Livid, Stormy, Frustrate, Torment, Vex, Annoy, Peeve, Fret, Hassle, Harass, Plague, Molest, Torment, Displease, Dissatisfied, Displeasure, Antagonize, Antagonize, Ruffle, Trouble, Perturb, Upset, Disconcert, Disconcert, Confuse, Fluster.
Using all these I asked NVivo to code any passage that has any of these words as ‘anger to check’. This gave me one cache of passages where anger may be expressed in any form. Using this significantly narrowed down cache, I did a manual check to remove irrelevant coding. Wordnet can be used similarly without NVivo in a range of other qualitative analysis software. Infact, it can also be used in MS Word or any primitive text editor that has a find and replace function.
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