Time Magazine Corpus

The Time Magazine Corpus digital tool compiles all Time magazine articles since 1923 and analyzes the changes in how the English language has been used and changed over time. This tool reveals how society and culture influenced trends in language with examples of words like “flapper”, “global warming”, and “hippy”. It’s easy to see how each of these words is associated with a certain period of time and how language changes with time. Additionally, researchers can view how parts of words have been used through time such as “-gate” as in “Watergate”, “-aholic” as in “shopaholic”, and common parts of words like “-dom” as in “Kingdom”.

Time Magazine Home Page

By simply typing a word into the search bar section titled “Chart”, an analysis of how often that word has been used in Time broken down by decade and its frequency is demonstrated by the varied shades of color. By clicking on the decade you want to analyze, results will show you the instances and issues the searched word appears. This could come back with over 100,000 results so the more specific and distinct a word the better results you’ll get.

Text analysis broken down by decades and then years

For example, typing the word “Mustang” in the chart section of the search bar quickly provides data on when the word is most frequently used. Not surprisingly, we see rises in frequency during the 1940s, when the P-51 Mustang was the most popular fighter of World War II, and in the 1960s, when the classic Ford Mustang was in its heyday. But the research doesn’t stop there, an additional click on the decade will show a second result broken down by each year in it. Here, we can see how in 1944 the word “Mustang” was most frequency used during the heart of World War II before dramatically dropping off in the post-war years. One more click will bring you to the lines in the issues published with “Mustang” in it displaying how useful this tool would be in researching this subject. However, by clicking the “List” part of the search bar, the results will take you directly to all the lines the word was used throughout history with no analysis of frequency through time. A third option is to click the ”Collocate” section of the search bar which allows you to search two words and get results to the times they were used near each other further narrowing results. By searching “Mustang” and “Germany”, you may be surprised to learn the two words only appear once near each other in a 1942 issue.

Thankfully, this tool acts as a Control+F search for the entirety of the Time magazine collection. I acclimated myself to this tool and found its usefulness far quicker that the Voyant tool because it is easier to navigate. The “Help” page was shorter and more concise providing examples of how the tool can be used and links to search result examples to demonstrate how the directions can be applied. One drawback for this tool is the need to register with an account and link your account with your university where as Voyant did not require that to use the tool.

Tour “Help” Page

Like the Voyant Digital Tool, the Time Magazine Corpus is hard to navigate and even harder to understand how to use. A very simple site and slow to load, the tool offers unbiased and accurate results that can be used to help researchers know where and when to look. Researchers now have the ability to contextualize language and pinpoint the areas they should look into. A very useful tool to analyze cultural shifts through language, this tool can clue us in on how fickle language is.

Voyant Tools

Voyant Tools is a web-based text reading and analysis environment. It is a scholarly project that is designed to facilitate reading and interpretive practices for digital humanities students and scholars as well as for the general public.

At first glance, it is unclear what this research tool is, how to use it, and what to take from it.

Voyant Site Home Page

After confusingly typing a word into the text box and clicking reveal, I found myself even more at sea by all of the analysis available if the site is used properly. The “Help” button is represented by a questions mark link that will redirect you to another overwhelming page of information seen below (Just look at all of those files to sift through). Any new user to this tool will undoubtedly need to spend some time navigating the site and learning all the potential text analysis available. The site is not particularly pleasing to the eye (Though I am not tech savvy so take what I say with a grain of salt).

Although, once the user inputs a URL into the initial text box (the way I should’ve started), a flurry of text analysis and data is immediately available. I copied and pasted the URL to the Wikipedia page on the P-51 Mustang as an example. Here you can view the frequency of key words in the text in the form of a word cloud, in graphs displaying in which parts of the text the word appears most, and a flurry of other available data with multiple ways of viewing that data.

Again, to really understand how to properly use this tool to its full potential, you’ll have to spend a bit of time reading through the descriptions of each option available to understand how to apply this site towards your research. Thankfully, the “Help” page is thorough and any information you may need can be easily accessed.

Researches may be interested in creating a “corpus”, which is a set of documents or URLs analyzed together. The tool is meant for humanities scholars to quickly analyze several texts by revealing trends, similarities, and distinctions. Hopefully, it will direct the scholar to ask questions of what the analysis can tell you, but its primary function is to be used as a tool for exploration and to assist with interpretative practices. The digitalization of history will save scholars time combing through countless texts and sitting in archives or libraries with a stack of books. The tool can also be used in different languages so it is not limited to just English. According to the tutorial and workshop page, an extensive workshop on how to use this tool can take an entire day signifying how complex accurately using this tool really is.

I believe there is a bit of irony in the digitalization of history as I chose to study humanities because the STEM field was always my weakest subject, and yet, I am again trading hardback books for digital tools. Despite my best efforts, technology is working its way back into my studies!

The Programming Historian

The Programming Historian is a website which publishes “novice-friendly, peer-reviewed tutorials” designed to help teach historians “digital tools, techniques, and workflows.” It is aimed at helping historians who identify as “technologically illiterate” to become programming historians. If you’re a historian and you want to know how to set up an Omeka site, or edit an oral history using Audacity, then The Programming Historian is a place to learn how and where to get started.

Over half of the lessons have been translated into Spanish. If you speak French, you’re out of luck at the moment.

Clicking on the English-language portal presents us with three options: we can Learn, we can Teach, or we can Contribute. Learn takes us to the lessons and Contribute provides links to pages with information for those interested in writing a lesson or becoming one of the reviewers. Teach has little beyond a link to provide feedback on ways to make the lessons better suited to being used as teaching tools. We’re going to Learn today.

Clicking on learn brings up all the lessons that you can access. There are 78 lessons available in English, which is quite a few to browse through.

The Programming Historian provides a few ways to organize the lessons to make it easier to find what you’re looking for. At the top, you can click on buttons to display all the tutorials that are tagged with one of five categories: Acquire, Transform, Analyze, Present, and Sustain. 30 lessons fall under the category of Transform, making that the largest of the five categories.

The next way to sort the lessons is by more specific criteria: for example, you can click to see all the lessons tagged with “Web Scraping” (only 6) or lessons that have to do with the  programming language Python (19 lessons – second only to “Data Management”).

Finally, you can sort the lessons by their publication date or by their difficulty. Lessons are given a difficulty – Low, Medium, or High. These difficulty lessons appear to be assigned based on the difficulty of the subject matter covered by the lesson, not the difficulty of using the lessons to learn the programming tool.

Here’s half of the lessons tagged with “Digital Publishing”

Let’s click on the lesson “Up and Running with Omeka.net”. This is a lesson designed to help historians set up their own content on Omeka.net.

The lesson is all text and images – no video or audio. The lesson reads like a longer version of one of our digital tool reviews, featuring walkthroughs of how to use the digital tool. When I say “longer,” I do mean significantly longer – here is the table of contents for the Omeka.net lesson:

And here is what the content of the lesson looks like:

The lessons all seem well-written and informative. However, they are not infallible: several lessons have notifications that reviewers have caught inaccurate information. Rectifying these errors is dependent on the website administrators contacting the authors and then having the authors correct the mistakes in their lessons.

Overall The Programming Historian seems to be a very helpful resource for any historian looking to expand their technical skills.

Digital Tool Review: Wordle

Wordle is a simple program (from the user side – I don’t know enough about coding to judge whether a lot is going on under the hood) which creates word clouds. Word clouds, for the unfamiliar, are a way of visualizing which words are used or found most frequently in a given text. Word clouds have become very fashionable in all sorts of presentations, because they allow a presenter to illustrate the key or central themes of a piece of text in a very easy-to-understand visual format. A word cloud is both a means and an end. A presenter might cite a statistic which is difficult for a listener to comprehend. Showing a word cloud dominated by a word presents the same information in a more visually striking way.

Here’s an example. This is the Course Description for History and New Media course:

To use Wordle, I downloaded the Mac app from the website. The web browser version will do the same thing as the downloadable app, but it relies on a piece of Java which many browsers no longer support. The app also requires Java but the software it needs is still supported and can be downloaded as an update from Java for free. I copied the text of the course description and then pasted into the text box which appears when the app is launched and hit “Go.” This generated the word cloud. Words which are used more often will be larger, so whatever words are the biggest are the ones used the most. Here’s that same text in word cloud form:

Wordle has several benefits for presenters: it is free, and usable on both web browsers or as a downloaded application. It does the computing and graphic design needed to produce a word cloud; a presenter who doesn’t have the time or resources to create a word cloud themselves can simply copy-and-paste text and then choose from a variety of styles and fonts. Using the simple drop-down menus, the creator of the world cloud can opt to remove common words in a number of languages. This ensures that the word clouds aren’t dominated by words without serious historical meaning, like “the.” You can also alter the graphic design of the word cloud in a number of ways: you can adjust how many words are included in the word cloud and how the words are arranged.

For an example of how Wordle might be used in a presentation, I decided to input the text of two related documents: the Declaration of Independence and the Constitution of the United States (amendments not included). This could be used by a scholar of early American history to illustrate the similarities and differences between the two documents.

Here is the word cloud that Wordle generated from the Declaration of Independence:

And here is the one generated from the Constitution:

A presenter could point to words which appeared in both word clouds, such as “States,” as well as illustrate the differences between the two documents. By altering the number of words included in the word cloud, presenters can make these contrasts even more obvious. Having these two images in a presentation would enhance its educational power, especially for visual learners.