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• What kinds of data can you analyze using your suite of tools?

Retrieve data from NY Times articles

• What kind of information can you extract from the data?

Visual forms of the data presented. This includes; word frequencies, amounts, geographical distribution, statistics, etc.

• What kinds of questions can you ask of your data using text analysis and data visualizations?

 To simplify and create discussions. This tool has the ability to demonstrate different visual forms of data. For example, a word tree can be used to simplify text and gives you the ability to search for a certain point, or word.

• What hidden patterns are revealed using text analysis and data visualization?

The hidden pattern was revealed through the different forms of visual data available. A word cloud represents the range of word frequencies while a word tree represents the relationships of words and the sentences they appear in.

• Who would be most likely to perform this kind of text analysis or data visualization

Anyone who is trying to specify a certain part of a text or statistic. This tool would be ideal for accumulation information for a presentation or skimming through an essay to pick out main points and/or words. 

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Why did your group choose the (type of) data/texts that you did?

 My group chose the President Obama’s Inaugural speech because the tools that we were provided to use did not give a good range of useable data forms. This tool became very limited to the articles that it provided for us. The type of text we chose allowed us to test and use different visual formations apposed to the other articles, that were limited to mainly text clouds. 

What parts of the tool did you use?

We only were successful by using word clouds and word trees, as I said above, the tools were limited to certain articles, unfortunately.

What did you find out about these texts?

We looked at the use of certain words within the text and its relation to the article.  

Which elements of the tools produced the deepest kinds of analysis (i.e. which were the most useful)?

The most useful kind of text analysis would be a word tree. A word tree demonstrates relations and connections between words and the article. This tool is great for picking out points of an article

For my Text analysis and Data visualization I will be focusing on Alice in Wonderland from the Project Gutenberg cataloge. I will be creating a Wordle to express different colors and word frequencies, a Word Tree to show connections between frequently used words and lastly extracting data manually.