This chapter is focussed on giving a brief introduction and explanation of the different visualizations that are concentrated on the field of text visualization. The chapter is an excellent resource on how visualizations or specifically different types of visualizations can be applied to do data mining on a block or documents of text.
The chapter further discusses about visualizations which are used for text mining. Such visualizations are very interesting because they establish a relation between two or more documents with a specific string or same phrases. The next kind of visualizations mentioned are related to word count an word frequencies. According to me, these visualizations are the most useful in today's digital world. With the expansion of digital matter and media, there is an ever-growing need of an efficient way to analyse a-lot of information quickly. Word-Cloud or Tag-cloud allows us to visualize digital textual matter efficiently by highlighting the most important or most mentioned phrases or words in the matter. Wordle is an excellent example of such visualizations.
The chapter finally mentions about visualizations related to citation and literature relations. These visualizations are a bit complex and difficult to understand but nonetheless extremely useful. The chapter could have explained the examples related to these visualizations more as I couldn't appropriately visualize how useful the information portrayed by such applications could be.
Overall, the chapter gives a very good explanation on the various visualizations related to textual data and it is very interesting to learn of the the different approaches made on the same 'dataset' and how each of them differ in their own unique way.
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