In this article, we want to share what semantic analysis is, the importance that it has to marketers and what it means in the context of machine learning and data science.
In summary, semantic analysis means to use the contextual clues surrounding the words and phrases of a text to better understand the practical meaning of the content of that text. This is something that, as humans, we do really efficiently and almost unconsciously.
Machines have historically failed at this because they lacked that ability to determine what is relevant and why. Advances in Machine Intelligence and Natural Language Processing (NLP) have impacted deep semantic analysis heavily through advanced algorithms, powerful computers, and a lot of practice, machines are getting so much better at it.
What are the applications of machine-driven semantic analysis?
- Get important and useful information from large bodies of unstructured data
- Find answers to questions without asking humans
- Understand the meaning colloquial sentences in online posts
- Uncover concrete meanings of words used in foreign languages mixed with our own
Why is semantic analysis so important to deliver relevant content?
Semantic analysis is really relevant for the marketers as you get real information regarding what are the users telling about saturation in the company process that is more relevant than one another. Get important and useful information from large bodies of unstructured data; find answers to questions without asking humans, understand the meaning colloquial sentences in online posts and uncover concrete meanings of words used in foreign languages mixed with our own.