LangGraph involves combining the principles of graph structures with natural language processing. It focuses on representing words, phrases, or entire texts as nodes within a graph, with edges showing relationships and contexts. This approach aids in identifying patterns, understanding contexts, and making predictions. It's typically used in applications like semantic search, sentiment analysis, and knowledge synthesis, where understanding the interconnected nuance of language is crucial.