Abstract:

Text mining is the analysis of unstructured (text) data in the natural language text using various methods, tools and techniques. Today, most organizations and organizations collect and store large amounts of data on data boards and cloud platforms. These data continue to rise as a base, with the arrival of new data from more than one source. It is difficult for companies and organizations to store, process and analyze large amounts of text data using traditional tools. Today, thanks to developing software such as Tableau, these problems have disappeared. The aim of this study is to statistically identify the heroes and events in Shakespeare’s works with the text mining method and to provide some forecasts to literary workers. For this purpose, the study, using Tableau software, applied the method of word frequencies, visualization and accumulation analysis to the Shakespeare data set located in the substructure of Google BigQuery. The collection analysis found that the word "Hamlet" was at the heart of all works and that Hamlet was Shakespeare's important work. Moreover, in the work of "Romeo and Juliet" respectively; "Romeo", "Juliet" and "Love" were found as commonly used words. These findings have come to the conclusion that the main characters of the work are "Romeo" and "Juliet" and the theme is "Love".

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