Text Mining Simplified – IPL 2020 Tweet Analysis with R
This article was published as a part of the Data Science Blogathon.
Text mining utilizes different AI technologies to automatically process data and generate valuable insights, enabling companies to make data-driven decisions.
Text mining identifies facts, relationships, and assertions that would otherwise remain buried in the mass of textual big data. Once extracted, this information is converted into a structured form that can be further analyzed, or presented directly using clustered HTML tables, mind maps, charts, etc.
Advantages of Text Mining
Text Mining saves time and is efficient to analyze unstructured data which forms nearly 80% of the world’s data.
- Text mining can help in predictive analytics.
- Text Mining used to summarize the documents and helps to track opinions over time.
- Text mining techniques used to analyze problems in different areas of business.
- Also, it helps to extract concepts from the text and present it in a more simple way.
- The text which is indexed using Text mining can be used in predictive analytics.
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