Co-occurrent

A term primarily used in linguistics, corpus linguistics, and related fields, 'co-occurrent' describes the simultaneous or frequent appearance of two or more linguistic items (words, phrases, morphemes, or other linguistic units) within a given text or corpus. This co-occurrence suggests a relationship between the elements, which can be semantic, syntactic, pragmatic, or simply a matter of chance. The degree of co-occurrence is often quantified using statistical measures to determine the strength of the association. Identifying co-occurrences helps researchers understand how language functions, how meanings are constructed, and how words relate to each other in actual usage. The study of co-occurrence is fundamental for tasks like building dictionaries, identifying collocations, and analyzing textual patterns. The relevance of co-occurrence varies across fields. For instance, in sentiment analysis, co-occurrence of certain adjectives and nouns might indicate positive or negative sentiment.

Co-occurrent meaning with examples

• In the analysis of a large online news corpus, the words 'climate change' were found to be highly co-occurrent with phrases like 'global warming,' 'environmental impact,' and 'fossil fuels.' This suggests a strong semantic relationship among these terms and highlights key themes.
• The lexicographer noticed that the word 'beautiful' was often co-occurrent with words describing nature, such as 'scenery,' 'garden,' and 'sunset.' This co-occurrence helps inform the definition of the word and its typical usage within various written contexts.
• In a study of medical records, symptoms like 'fever' and 'cough' were co-occurrent significantly more than expected by chance. This co-occurrence led to further investigation to determine the underlying cause of these associated symptoms.
• A computational linguist employed co-occurrence analysis to identify the most frequently associated words with 'artificial intelligence.' The results showed high co-occurrence with terms like 'machine learning,' 'algorithms,' and 'automation,' indicating key AI subfields.
• The marketing team used co-occurrence to analyze customer reviews. They observed that the word 'expensive' was often co-occurrent with 'small' and 'quantity' when describing a new product, which allowed them to adjust pricing and market information.