Mallet Lab

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After using the Mallet Lab, it was interesting to see how straight forward, and easy to navigate it was.   After using the Topic Modeling tool, it was interesting to see a lot of the same words being used to describe certain sentences within the passage.  Above is the word cloud that is composed of the words I have uncovered from the Topic Modeling tool.  Most of the words that showed up multiple times were investigation, blood, crime, and murder.  The other words were used as well, but those three stuck out the most.

What I found most useful about the Topic Modeling tool was how easy it was to navigate.  Really, the only thing we had to do as a class was type in the amount of topics, and iterations and the system did the rest for us.  Overall, it was quite interesting to see the amount of times a word was used, and interesting to see how they put certain words together in a sentence (that did not thoroughly flow) to explain a certain topic.

Sherlock Holmes novels can sometimes be difficult to understand, but with the help of the Topic Modeling tool, it makes it a lot easier to understand exactly what topics are apparent within the novel/passage.   Most of the time, a lot of the words that are used are there to explain the theme within the passage.  For example: Sherlock Holmes is a detective, therefore it would make sense that a majority of the keywords used involved investigation, crime, and murder.  This helps the reader ultimately understand without reading the full novel that the book/passage is about investigative activity, which can be extremely useful.

Overall, topic modeling is a very useful tool when it comes to literature, and opens up the eyes of the reader to overlook some of the more unimportant words, and focus on the topics and themes that either reoccur, or explain the story.

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