The rise of social networks has led to an increase in unstructured data available for analysis, with a large proportion of this data being in text format such as tweets, blog posts, and Facebook posts. This data has a wide range of applications, for example it is often used in marketing to understand people's opinions on a new product or campaign, or to learn more about the target market for a particular brand.
When dealing with large volumes of unstructured text data, it can be difficult to extract useful information efficiently and effectively. There is almost always too much data to read through manually, so a method is needed that will extract the relevant information from the data and summarise it in a useful way.
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