I used Voyant to analyze the following online texts/sites:

The New York Public Library Digital Collections :Act Up New York Records

National Aids Memorial: History of the Quilt

New York City Aids Memorial : HIV/AIDS Timeline

Britannica: ACT UP article

Very easy to use and create visualizations such as cirrus, termsberry, word links, and word trends. It was fun to see similarities between texts and sites very quickly. I thought I would see certain words regarding race, sexuality, more healthcare terms like illness, drugs, certain medical professions, to be more common but wasn’t the case. Also, different entities, like the FDA, government bodies, maybe other activist groups to have come up as well. Furthermore, it was interesting to not see common names of people who were pivotal to the movement.

I was trying to see how I can link terms together, for example “new” and “york” to be linked as a phrase instead of individual words. In the termsberry, cirrus, and trends you see the words separately.

In all, I enjoyed using this tool very easy to add in more sites, to hover over the tools and see the information. I would say the tool is very useful, insightful, and efficient in producing the data.

While continuing to play with this tool, I saw the feature of scatterplot, in output you can select options of different unsupervised learning methods like document similarity, PCA Analysis, Component Analysis, and t-SNE. In the graph below you can see how close together points “new” and “york” are, going back to the point of using the phrase new york instead of individual words.