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By Kilian Thiel & Lada Rudnitckaia, KNIME Sentiment analysis of free-text documents is a common task in the field of text mining. In sentiment analysis predefined sentiment labels, such as "positive" or "negative" are assigned to texts. Texts (here called documents) can be reviews about products or movies, articles, tweets, etc.
They were a televised series of cook-offs in which famous chefs rolled up their sleeves to compete in making the perfect dish. Based on a set theme, this involved using all their experience, creativity, and imagination to transform sometimes questionable ingredients into the ultimate meal. Hey, isn’t that just like data transformation? Or data blending, or data manipulation, or ETL, or whatever new name is trending now?
Practically everyone has heard of Little Red Riding Hood, a fairytale of an encounter between a young girl and the Big Bad Wolf. One of the most popular versions of this tale was written by the Brothers Grimm. But what has a simple folk tale got to do with text stream visualization? And what is stream visualization? Stacked area charts, or stream visualizations, are very useful to show how topics in a single document or set of documents change and develop over time.
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