Language heuristics is used more intensively by search engines, content aggregators and many others not only in depth, complexity, educative and quality terms but also in content analysis regarding suitability, commentary, news and other sectoral value positions. Because automatic analysis of language heuristics saves time, increases convenience, optimises indexing, determines usability, cause increased levels of accuracy on many levels and so much more, it is the next big tech thing.
As an example, the website unpartial.com analises the perspective and opinion of individual article content. Commercial (as well as free) language heuristics web functionality has been around for some years now, notably media houses would use online content analysis tools to classify, understand and control published content for various reasons but mainly to ensure that content complexity is suited to the targeted consumption audience.
Search engine giant, Google, is also starting to understand content better. Google is already a master of links and content, understanding the words used in content and more, but with advances in language heuristics also applied to search and locality the results returned to users are of an increasingly higher quality. This can more easily be seen on Google by adding some contextuality to programming resource searches, for example searching for a specific method of a join for a specific version of PostgreSQL or looking for examples of application of a specific function. The Google results have been steadily improving over the past few years as the results related to such searches are more frequently of a higher quality and includes more than just returning results based on word usage and links to content.
