Lexical affinity is a term that is used to describe how two or more words are related to each other in terms of meaning. The term is often used in the context of text analytics, where it can be used to determine the relationships between words in a piece of text.
Lexical affinity can be thought of as a measure of semantic similarity between two words. The idea behind lexical affinity is that words that have similar meanings are more likely to occur together than words with dissimilar meanings. This principle can be used to identify groups of related words, or to find new associations between words.
There are a number of different ways to calculate lexical affinity. One common method is to compare the co-occurrence of words in a piece of text. This can be done by looking at how often two words appear together in a corpus of texts, or by looking at the co-occurrence of words in a specific text.
Another common method is to use a thesaurus to identify words that have similar meanings. This approach relies on the fact that words with similar meanings will often be listed together in a thesaurus.
Lexical affinity is often used in combination with other methods, such as topic modeling, to more accurately identify relationships between words. It can also be used on its own to find new associations between words.
Lexical affinity vs other methods
Lexical affinity is just one method that can be used to determine the relationships between words. Other methods include topic modeling, word embeddings, and semantic networks.
Topic modeling is a method of identifying groups of words that are related to each other based on the context in which they appear. This approach can be used to find new associations between words, or to group together words that have similar meanings.
Word embeddings is a method of representing words in a vector space. This approach captures the relationships between words by their position in the vector space. These relationships can then be used to find new associations between words, or to group together words that have similar meanings.