Text analysis is a field that I didn’t thought about it before this class. For me its interesting too discover new information on data already available to us: text mining Twitter posts and Facebook comments could give an impressive amount of information to researches and businesses equally.
This chapter provides a snapshot of visualization tools applied to text: visualizing text mining results, document concordance and word frequencies, and literature and citation relationships. For text mining many tools are shown including the JIGSAW. Word concurrence visualizations are by far, my favorites: the DocuBurst it’s impressive, TextArc looks very useful, but very hard to display, due to it’s size; of course, zooming controls. Tag clouds are always fun, and the “Word Nebula” project done by my fellow classmates seems a right step forward.
Finally, the chapter shows visualization tools for relations in literature. One example, is a graph showing relationships among scientific disciplines. Just thinking about a table showing the same data, makes me see the importance of visualization in this and other cases.
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