An open source, web based graphical text analysis application. Upload a text, or find one online and start your analysis with things like word frequency lists, frequency distribution plots, and keywords in context. Built for the digital humanities, it’s applications can definitely reach further.
For this activity you will analyze a text using Voyant.
Find a text you want to analyze. If you don’t already have one, go to Project Gutenberg Canada and select a text. What the site lacks in aesthetics it makes up for in content!
Head over to Voyant Tools and plug in your text https://voyant-tools.org/ All you’ll need is the url for the text, for example, either the html or the epub link from Project Gutenberg Canada.
Explore the results.
Get in depth guidance through the Voyant Tools help pages https://voyant-tools.org/docs/#!/guide/start
For Example
A text analysis of the novel Crossed Swords by Alloway, Mary Wilson using Voyant Tools
Complete this Activity
To complete the activity, share the following:
- Using the Export a URL (top right menu) function and copy and paste the URL in the comments.
- Share some brief thoughts and ideas about the tool.
Image Credit: Image used on featured image:Twitter wordcloud by JSutherland (WMF) (CC by SA 4.0)
I used Voyant to look at the Great Gatsby manuscript, and I think that it’s telling that the most commonly used words are the characters’ names, and that the usage of “Gatsby” peaks roughly midway through the text, whereas “Tom” peaks shortly after, which suggests the drama and events of the narrative. For this data set I’m not certain what much more could be said on this topic, but perhaps with some maneuvering one could determine what word associations occur, which could be enlightening.
I don’t know if this will work (the link to embed an image of the graph is too long for this text box). Here goes nothing! https://voyant-tools.org/spyral/?run=true&inputJsonArrayOfEncodedBase64=%5B%22JTNDaDIlM0VTcHlyYWwlMjBOb3RlYm9vayUyMEltcG9ydGVkJTIwZnJvbSUyMFZveWFudCUyMFRvb2xzJTNDJTJGaDIlM0U%3D%22,%22bG9hZENvcnB1cyglMjJmMGE2ZmFhMzhjNmUwYTdjOTUwMjQ1MTY4NmY0ZDIxMiUyMikudG9vbCglMjJDaXJydXMlMjIlMkMlN0IlMjJ2aXNpYmxlJTIyJTNBMTI1JTdEKSUzQg%3D%3D%22%5D
I’ve used Voyant in my own work before (much more data-centric), so it was fun to get to explore what the tool could do for analyzing fiction instead! I explored Christopher Logue’s War Music (a retelling/reimagining of the Iliad) and really enjoyed seeing that ‘god’, ‘lord’, and ‘king’ were the most common words, given that the stated purpose of the retelling was to ground the story in humanity and violence – despite this, the influence of divine and grand figures still predominates, at least in frequency. I really appreciate Voyant Tools as a free, user friendly tool, particularly the many options to customize outputs.
My outputs can be found here: https://voyant-tools.org/?corpus=cbcf880adbf3128272b5979dfe929272&panels=cirrus,reader,trends,summary,contexts
Corpus Linguistics can provide valuable insights. I have used other tools, but can’t recall using Voyant recently. I decided to use it for the three first chapters of the novel “The HAte U Give” by Angie Thomas. Although this might be considered a grade 11/12 high school-level novel, I have used a few chapters with international students at the post-secondary level and was curious to apply the Corpus Linguistics tool to it. The most frequent words in the corpus were like (67); daddy (65); kenya (59); don’t (56); i’m (56). I found it interesting that the word “don’t” was so common. it seems to be associated with teenager/young resistant adult behavior and contexts. I’m not sure what else can be said about the results. My results can be found here: https://voyant-tools.org/?panels=cirrus%2Creader%2Ctrends%2Csummary%2Ccontexts&corpus=12062061e102f4446e17b5ff30e84375
I used the Voyant tool to look at 𝗧𝗵𝗲 𝗖𝗮𝗻𝗮𝗱𝗶𝗮𝗻 𝗖𝗵𝗮𝗿𝘁𝗲𝗿 𝗼𝗳 𝗥𝗶𝗴𝗵𝘁𝘀 𝗮𝗻𝗱 𝗙𝗿𝗲𝗲𝗱𝗼𝗺𝘀. This is a short but, obviously, very important document. I am currently writing on Freedom of Expression (for K-12 teachers in the off-duty context) so I was curious to see if the tool would highlight anything interesting.
Adding 𝘊𝘢𝘯𝘢𝘥𝘢/𝘊𝘢𝘯𝘢𝘥𝘪𝘢𝘯/𝘊𝘩𝘢𝘳𝘵𝘦𝘳/𝘳𝘪𝘨𝘩𝘵𝘴/𝘧𝘳𝘦𝘦𝘥𝘰𝘮𝘴 to the Stopwords, the word cloud reveals the importance given specifically to New Brunswick within the “Official Languages of Canada” section of the Charter. Visualization of text here: https://bit.ly/3p7l8EK
I was interested by the appearance of the term “respect”: looking closer, it is used only as synonymous with 𝑐𝑜𝑛𝑐𝑒𝑟𝑛𝑖𝑛𝑔 than referring to 𝑒𝑠𝑡𝑒𝑒𝑚.
I have experience of corpus linguistics from my MA thesis [https://ulir.ul.ie/handle/10344/6654] when I used 𝗪𝗼𝗿𝗱𝗦𝗺𝗶𝘁𝗵 𝗧𝗼𝗼𝗹𝘀 for analysis. This tool seemed quite cumbersome at the time and, in contrast, Voyant is a handy tool for getting a quick visual overview of a text with a whole lot of other features “under the hood” that I need to explore. 5/7 would recommend.
This is the first time I am using a visual text tool. It was simple to use and I like the functionality of the tool. it is free and user friendly. As an instructor, it can provide a wonderful visual aid for keywords. Many students respond to word clouds. I analyzed the book Looking Forward by Franklin D. Roosevelt. The text chosen by this tool were in sync with what I associated with this book, for example, government, economic and people to name a few. The stop list work well and I was edit as needed.
My results can be found here:
https://voyant-tools.org/?corpus=3669e5ed70fed12c64ef0a7450b28e91&stopList=keywords-0d641b30f522c74741398d87f8c3049a&panels=cirrus,reader,trends,summary,contexts
This was also my first time using this visual text tool. The book that I analyzed is: The Political Madhouse in America and Nearer Home. A Lecture, by George Bernard Shaw. I was curious to see the phrases that were used. It was interesting to note the phrases and how many times they appear in the corpus and the correlating graph. This would be a handy tool to see what kind of phrases were used thirty years ago and compare it to today’s books on the same topic.
The phrases can be found here:
https://voyant-tools.org/?corpus=c1123ca1bc52394ed867fa334c235a88&view=Phrases
This tool is very easy to use and depending on the nature of the text, it could yield some cursory insights.
I used Recommendation on Open Educational Resources (OER) from UNESCO as my sample text https://voyant-tools.org/?corpus=64da14c320d89ca3f5de810b419ef58e&panels=corpusterms,reader,trends,summary,contexts I was curious to see what the interplay was among certain concepts central to OER such as resource quality, accessibility, capacity to create OERs and their sustainability https://voyant-tools.org/?corpus=64da14c320d89ca3f5de810b419ef58e&query=quality&query=accessible&query=sustainability&query=disabilities&query=capacity*&mode=document&view=Trends I
What I can glean from the visualization is that ‘quality’ is used as an overarching concept that weaves in through the whole document. Surprisingly, the concept of sustainability which seems essential to ongoing quality assurance and reusability of OERs has a relatively subtler presence and does not figure prominently as an ongoing thread throughout the entire document.
There is also a glitch in the interface with colour coding, where “accessible” points are interpreted as “quality”.
The tool reminded me of http://tapor.ca/home led by University of Alberta. It is a database of various tools used in digital humanities.
http://tapor.ca/tools?page=2&query=open%20source&attribute_values=10 all tools can be filtered by type of use, for example open source or creative commons.
This was also my first experience with the Voyant tool. I found the graph with relative frequencies and document segments especially interesting. The TermsBerry tool was also a useful visual, though it was harder to identify patterns or trends in word use. The visuals produced are from Johnathan Swift’s A Modest Proposal: https://voyant-tools.org/?corpus=86bb11cc583ab84083fb69ce8f66b024
I used the manuscript of THE CASE-BOOK OF SHERLOCK HOLMES for this exercise. It was interesting to see different keywords highlighted in each chapter (although I tried only two chapters in this exercise). As it is a detective story, it would be interesting to investigate what words are more frequently used in each chapter to see the author’s intention of the storytelling.
Chapter 1: https://voyant-tools.org/?corpus=23d551c942bdd49fb1bc6b24f02f9701&panels=collocatesgraph,reader,trends,summary,contexts
Chapter 2: https://voyant-tools.org/?corpus=1fe414744b921159052dd782a57cbeb7&panels=cirrus,reader,trends,summary,contexts
testing
I used Arthur Conan Doyle’s manuscript, “The Case-Book of Sherlock Holmes” for this exercise. It was interesting to see different keywords highlighted in each chapter. If we use this method in analyzing keywords (and their relationships) in each chapter, it may help us understand better the intention of the author’s word choices for his detective storytelling.
Chapter 1: https://voyant-tools.org/?corpus=23d551c942bdd49fb1bc6b24f02f9701&panels=cirrus,reader,trends,summary,contexts
Chapter 2: https://voyant-tools.org/?corpus=1fe414744b921159052dd782a57cbeb7&panels=cirrus,reader,trends,summary,contexts
So cool!
I analyzed the UBC strategic plan and the YA book Hatchet, by Gary Paulsen.
https://voyant-tools.org/?corpus=297b94124e94904d9c64e4759569f333&panels=cirrus,reader,trends,summary,contexts
The three most common words in UBC’s strategic plan are UBC, strategic and plan, which made me chuckle.
In Hatchet, a book that is so much about interiority, the most common word was: thought.
I can definitely see applications on this when I teach close reading.
I used this tool to analyze some of my own energy-related blog articles on an industry website.
It’s interesting to see that using these common trends in research and industry can be easily identified. This can also be very helpful in comparative studies and finding interrelationship in different fields
I used this tool to analyze the info page for my PhD program. Unsurprisingly, research figures prominently, along with student(s)/course/PhD. It would be interesting to see how similar or different info pages in comparable programs would be using this tool. Maybe they would all look the same, or maybe the messaging in more learning-centred (rather than research intensive) universities would look different.
https://voyant-tools.org/?corpus=2af7a2962ab7088a157a75365bd33e7c&view=Cirrus
I have never used the Voyant tool before, however it was interesting to see how it analyzed the URL as well as the data it analyzed from the text, which I have provided below. This tool would be extremely helpful for those looking to analyze multiple texts or for an in-depth analysis of a particular text.
https://voyant-tools.org/?corpus=241a17a91356e1890dafdbed3449782e
This corpus has 1 document with 28,373 total words and 4,952 unique word forms. Created now.
Vocabulary Density: 0.175
Average Words Per Sentence: 21.8
Most frequent words in the corpus: bay (167); pg (135); radisson (125); company (106); french (94)
I chose the text from Sylvia Plath’s “Bell Jar” for this activity. It was quite interesting to see what the most frequent words were in the text and also to be able to have the actual number of times they are used calculated along with a word cloud visualization. “Like,” “said,” “thought,” “buddy,” and “doctor” were the top 5! Such tools enable us to see trends in different languages, time periods, regions, etc. and then compare that information to get a better sense of the culture, politics, and themes of those times and how it varied between various groups (i.e. socioeconomic status). Ultimately, this information tells its own story.
https://voyant-tools.org/?corpus=bf50e01f61b0ad6711a684f24a995538&view=Cirrus
I used this tool to analyze some of my own energy-related blog articles on an industry website.
It’s interesting to see that using these common trends in research and industry can be easily identified. This can also be very helpful in comparative studies and finding interrelationship in different fields
My link was not posted last time
https://voyant-tools.org/?corpus=ff825a011824660c8f6cfb8780394d0b&panels=collocatesgraph,reader,trends,summary,contexts
I wish I’d known about this when analyzing narratives for the purpose of my M.A. thesis (and as an undergraduate student in English Literature for that matter!)- what an interesting tool. This could be used to really quickly and succinctly summarize key, core repeated concepts in a work of writing; to identify themes as they play out at different points within a work; and to draw connections between multiple works for the purpose of comparison and analysis. I see applicability with narrative analysis as a research method.
I looked at a few pieces: to name a few, Milton’s Paradise Lost (“heaven” and “god” were on the top 5 words), and Ian Fleming’s From Russia With Love- linked below, as is to be expected, “Bond” was the most recurring word).
https://voyant-tools.org/?corpus=c225a71580dd2b9aa3900e7557dc7cb7
This is my first time using the tool too! I found it very easy to use and user-friendly. It provides a similar function compared to NVivo. I used an very easy to read article from my student’s tutor section. It’s an article related to Christmas and activities we can do during the pandemic. Not surprisingly, “Most frequent words in the corpus: holiday (14); christmas (12); family (6); day (5); like (4).” I also like how the words are linked to each other. I found this tool a useful one to have a quick look at the text before diving deeper into it! Here’s my output: https://voyant-tools.org/?corpus=8cca659661331e7dec7650337e988507
I chose War and Peace, which I am currently reading. For a book that’s described as a history of Russia, it was funny to see that “French” figured far more prominently than anything obviously Russian. The 5 most prominent words were: “said,” “prince,” “Pierre,” “Natasha” and “Andrew” – unsurprising. I did get a lesson on data verification, however: when I toggled to the DreamScape, which pins all mentions of cities on a world map. The tool assumed that the “St Petersburg” and “Vienna” mentioned in the book referred to St Petersburg, FL and Vienna, VA. Anyone who was trying to visualize the locations all of the happenings in War and Peace would have to clean up of what Voyant produced.
https://voyant-tools.org/?corpus=3085585aa4364a4fedc3538e8c11224e
What a great tool! As a first-time user, I found it easy and straightforward to use: https://voyant-tools.org/?corpus=d0abcd3a7fcb0528b64164b6bac545df&view=Summary
This was a fun activity! I have used and seen simpler versions of word clouds before, but Voyant is such an interesting platform because it provides a bit more analysis about the different aspects of the text. The text I chose was The Lion, The Witch, and The Wardrobe by C.S. Lewis. Interestingly, the most common word was “said”, followed by the major characters’ names. I enjoy seeing the different trends in the text, document phrases, and more. Such a useful tool that, to echo others, I wish I would have known about sooner during my undergraduate degree! See the link here: https://voyant-tools.org/?corpus=4d730d931f874b9eb20be1cf8a567af7&panels=cirrus,reader,trends,summary,contexts
I used Marcel Proust’s Remembrance of Things Past — such a delightful piece of writing about the senses and memory. I played around with a number of the visual tools in Voyant and especially liked the Knots one. I can see how this might be really fun to use in teaching my qualitative methods class where students employ a variety of approaches to analyzing text and representing the findings visually. So many more options than just a word cloud! Here is my work https://voyant-tools.org/?corpus=cec4659825e828e98738b0fcd8600785
I used an essay (about 4000 words) I wrote last semester about people wanting to remove children from the Museum experience.
https://voyant-tools.org/?corpus=7fa2e3a55ab602310d804ed1bbae381e
The results were very interesting! I realized that I had used the word “museum(s)” over a hundred times! As well, my sentence length average way too long. While I think this tool could be slightly more user friendly, I think I will use this in the future to gauge my writing as a whole and help me become more mindful to what I am writing and how I am writing it. Also, to try and make my writing more concise yet meaningful, like whether I can say something in a more direct way, versus the longer and unnecessary way of saying something to perhaps meet a word count. (And it has definitely taught me not to say “museums” so much!).
This is the first time I use Voyant Tools, the timing coincides with my recent struggles in business communication. The analytics in the tools helps me discover of what is lacking in the text, and also it is easy to see the redundancy in the content. It can be a great analytical tool to me in the future.
Here is a short excerpt from [More Work for the Undertaker (1949) Wikipedia]
https://voyant-tools.org/?corpus=079d567c185f15aec83da22afd57a235&panels=cirrus,reader,trends,summary,contexts
This was the first time using a text analysis application, and it was surprisingly easy and intuitive to navigate. I used Voyant to analyze “One Hundred Years of Solitude” because I was interested to see what the most common word would be. Unsurprisingly, it was “Aureliano”. Although what yielded more interesting results was the TermsBerry function. In general, I see Voyant and other like tools being especially useful for linguistic corpus research.
My results are available at:
https://voyant-tools.org/?panels=cirrus%2Ctermsberry%2Ctrends%2Csummary%2Ccontexts&corpus=85bf7721bce73c7113f17492ba924136
I decided to use Shakespeare’s A Midsummer Night’s Dream, since I thought it would be a fun text to analyse. The five most common words are “love,” “Demetrius,” “Lysander,” “Hermia,” and “shall.” It was interesting but perhaps not surprising to see that “love” ended up being the most common word in the play. I was surprised to see “shall” as one of the most common words within the play, and that it had such steady usage throughout all the acts when compared to the other words. It makes sense, because “shall” is not a pronoun like character names. I believe that this tool could be useful for me in analyzing my word usage in my own writing, which would allow me to see how concise my language is along with what I tend to repeat that I may miss during proofreading.
My results: https://voyant-tools.org/?corpus=e15ff43947c706bdc719f05367ea67bf
I analyzed Thomas Moore’s Utopia. Not surprisingly the most common words were man, men, good, great, people. Interestingly, when I used the URL, one of the top words was “Gutenberg”. So I subsequently redid it, but by copying and pasting the actual text in, rather than supplying the URL.
https://voyant-tools.org/?corpus=12ef587234b02a16b8d4642d54c434c5
https://voyant-tools.org/?corpus=e789b06d5f52c485e083585b8fb11de4&panels=cirrus,reader,trends,summary,contexts
I’ve played around with Voyant before, but it’s been a while. I used George Orwell’s Animal Farm. The results were interesting, but maybe not all that surprising. It’s been a long time since I’ve read the book, but most of the most common terms are words you’d associate with an actual farm (types of animals, “fields”, “milk, “animal”, “windmill”, just to name a few). I suppose a takeaway here is that this example shows some possible limitations of using a tool like this for analyzing a work that relies heavily on symbolism. If someone unfamiliar with the book were to rely only on the word cloud, they might think it a book about about farming (though the inclusion of “Napoleon” as a top term might be confusing). That said, I could see how using a tool like this might be helpful when used in conjunction with a more traditional study of the text.
This was amazingly quick to do! Very interesting, I had not used Voyant before. Looking forward to exploring it more.
Here is my output: https://voyant-tools.org/?corpus=572331589620cd7e0675757ddcfeadd7&panels=cirrus,reader,trends,summary,contexts
This was my first time using voyant as well. I analyzed the UBC Indigenous strategic plan. I was interested to see that the words community and relationship were not as prominent as I would have expected. I am still pondering how this tool could be incorporated into my teaching, but it was fun to explore and play.
https://voyant-tools.org/?corpus=a863527af14b573c7fbd0596ef36bf7e&query=indigenous&query=ubc&query=plan&query=peoples&query=action&mode=document&view=Trends
This is a neat little tool! I explored Sir Arthur Conan Doyle’s “The Hound of the Baskervilles” for this exercise. The most frequent words are character names and words like “sir”, “man”, and “moor”. I was trying to think of ways that this tool could be useful. I’d be interested in a study that used this to explore gendered language in literature. I’d be interested in hearing applications for how this could be used. I love that it’s open source. https://voyant-tools.org/?corpus=6f42bb27587a9aba3792bc1a98be87c0&panels=cirrus,reader,trends,summary,correlations
The last book I read, Raymond Chandler’s ‘Farewell, My Lovely’ is dialogue-heavy (“said” is, uh, said more than twice as frequently as the next most used term). That on its own might isn’t all that interesting. Where I might start to take notice are the number of times terms like eyes or face or looked crop up, which is surprisingly high, which are elements of the text I might consider exploring further.
I am also reminded of the time I counted the frequency of the phrase ‘so it goes’ in Slaughterhouse Five for an undergrad paper. Voyant would have saved me some time there (and probably resulted in a more accurate answer).
https://voyant-tools.org/?corpus=d3f58e0149c6f22b0ae263c94fa5a87e&panels=corpusterms,reader,documentterms,documents,contexts
I analyzed a couple of emails I received to see if there was ‘something there’.
Here is the results: https://voyant-tools.org/?corpus=07256c0f9e41b757fa26894a3a9b5bb8&panels=cirrus,reader,trends,summary,contexts
I have explored Voyant before, and I really like how it allows you to get some ‘distant reading’. Meaning, you get to see some of what the text is about without reading it! I especially like that you can download any of the analyses and continue playing with the data with other tools.
I looked at Roughing it in the Bush by Susannah Moodie, which has two editions available through Project Gutenberg (1851 and 1872). I didn’t see anything that interesting in just looking at one, so I compared the two.
The first edition includes Canada as one of the most common words in the text, in large-ish type in the graphical display. The second edition, however, which was published in Canada, has it much, much smaller. I played around with the interface to see if there was a way to get the numbers behind these display differences and learned that if you type in the search box below the text box in the upper middle, it will show you the numbers that go with the term/phrase you type in. It turns out there are 197 mentions of Canada in the first edition and only 114 in the 19872 edition. This tool could be used to expose differences in language/vocabulary across editions, like from this I could now investigate why this discrepancy exists.
For my Voyant analysis, I used Project Gutenberg’s version of The Sun Also Rises by Ernest Hemingway. I’ve read this book in the past, so I thought it would be interesting to have some context added to the work. The words most frequently used were the characters’ names [brett (414); bill (334); mike (246)] and the words said (966) and went (298) which I thought aligned with what I remembered of Hemingway’s writing. Lots of discussion between the characters! It would be interesting to compare other works by the author to see how the number of unique word forms and total words are across books.
I have never used a tool like this before and I honestly thought it was so interesting! I think in my own work this is likely not very relevant, but I can definitely see how using this tool for textual analysis would be incredibly helpful (especially in literary studies). The fact that was relatively easy to use and free is also great for students.
Here is my link: https://voyant-tools.org/?corpus=2febd1ce24bf14c027dd297ab205fd2a&panels=cirrus,reader,trends,summary,contexts
This tool is amazing! I tried it out with a newly collected set of data (students’ responses to a prompt about what the major challenges were in a course) and I got all kinds of interesting outputs with just a click. However, I am posting my outputs from the abstract of an article that I was planning to read and I have not yet read: https://voyant-tools.org/?corpus=199facdff33368f0f2cb6b18d558a494
The output gave me a good sense for what the paper is about (better than what the title said), mean sentence length, etc. The correlations feature is great! Not necessarily relevant here for the paper abstract, but in looking at the students’ responses it is really helpful (e.g. high correlation between ‘quizzes’ and ‘helpful’, as well as between ‘questions’ and difficult’ and ‘time and difficult’) just by looking at that table I have a general picture of how the class felt about the challenges they encountered. Also, ‘difficult’ was the second most frequent word.
I did not know about this tool at all, and I will certainly use it now. One potential use is to get a quick, global look at the comments in my teaching evaluations at the end of term – a quick copy-paste and a click would give me the ‘gist’ of what the comments say, allowing to then go into the actual document with a focus on specific aspects that I would have picked out from this initial analysis. In terms of research, it can be of great help in the initial phases of a qualitative analysis, especially when not all collaborators on a project have access to proprietary software such as NVivo and atlas.ti What a great find!
I used Voyant to analyze my Master’s thesis, which was an analysis of a container port proposal at Port Alberni, BC:
https://voyant-tools.org/?corpus=7734f17c5e883c0f33f3313dfcb197f9&panels=cirrus,reader,trends,summary,contexts
Not surprisingly, “port” and “alberni” were the two most frequently used words, with “path” (the project name) and “container” being the 3rd and 4th most frequently-used words.
The document i used for analysis is a PDF and so the translation wasn’t flawless; the word “ay” shows up in my word cloud, partly because I reference the Huu-ay-aht First Nations on Vancouver Island, and partly because it is occasionally reading the “-ay” suffix in days of the week separately from the rest of the word.
https://voyant-tools.org/?corpus=f8bdc8715db8ace55d0a81e3ba364e87&panels=cirrus,reader,trends,summary,contexts
I explored The Judgement of Larose by Arthur Gask. Understandably, “larose” and “detective” were two of the most common words in the novel. Interestingly, “said” and “replied” were also among the most frequently used words in the book, indicating that it’s quite dialogue driven or at least dialogue-heavy.
I have actually used Voyant in an English class in undergrad to analyze digital texts. It provides unique insights into a text and especially helpful for evaluating a large volume of texts. It’s interesting to see what themes get highlighted through this quantitative analysis. English is a discipline very invested in doing close readings, but getting insight into a text from this more distant reading can also be valuable and interesting.
http://gutenberg.ca/ebooks/simcoe-proclam1792/simcoe-proclam1792-00-t.txt
Hello, I imported the above URL for the following item into Voyant, from Project Gutenberg.
“A Proclamation, To such as are desirous to Settle on
the Lands of the Crown in the Province of Upper Canada”
Author: Simcoe, John Graves (1752-1806)
Date of first publication: 1792
I was quite stunned by the simplicity of use of this program and how fast the results were presented.
I am not surprised that the most common word in the document is “shall” as this is an official document that deals with the rules and regulations (legalities) of land grants (patentees).
I looked at the frequency pattern produced by the most commonly used words in the document and not surprisingly there seemed to be a repetitive cadence/rhythm to the words used – that is, the words were repeated about the same amount of time and used at regular intervals.This speech almost appears to be following a template for an official/legal document.
The correlation, visualization and word tree tools were interesting. It certainly saves a lot of time for people to just plug in the URL and let the program do the work. As this document was not too long, it did not produce a lot of data., but what was there, was interesting. I certainly see the usefulness of this tool for a quick and dirty analysis in a study that might be looking at word use perhaps by participants of interviews or in surveys.
I wonder if perhaps there might not be other programs that provide even more tools for analysis or is it limited because this is a text analysis rather than a numerical data analysis?
This was a great tool to explore! I had not heard of Voyant before, but I could see it being useful as a way to get quick analytics summaries for different works, and also as an introduction to the capabilities of text analysis.
https://voyant-tools.org/?corpus=324d2b7de5fa14b4c82c1119e4e3efb1&panels=cirrus,termsberry,trends,summary,bubblelines
I decided to process Robert Frost’s West-Running Brook book of poetry. The words “brook”, “west”, “flowers”, “life” and “like” were the most frequent. With “like” ranking among the top words, exploring this term also allowed me to find different instances of simile in the text, so Voyant could also be used as a way of exploring literary devices used in writing. The TermsBerry option was great too, as it highlights words with an equivalent amount of occurrences as the word you have selected, giving more ways to contextualize word frequency.
I have used Voyant in previous class settings and always enjoy putting in new texts. For this activity, I used Tolstoy’s Anna Karenina. It would be interesting to compare different translations of Anna Karenina through Voyant to see if there are any substantial changes to the popular words. I found it comedic that my summary indicates “said” is the most commonly used word, since, I would argue, that word does not have a lot of literary value. Following “said” were the names of major characters in the plot. My favourite part of Voyant is the trends where you can see the frequency of mentions. I would be curious to see how this tool could be used in the social sciences or STEM disciplines.
https://voyant-tools.org/?corpus=ff0f1a00a8c67f467703065743493c3e&panels=corpusterms,reader,trends,summary,contexts
https://voyant-tools.org/?corpus=959dfba992aecec78d70dce921359f46&visible=45&view=Cirrus
I used this tool to explore the usage of repeating in a number of short fiction, though linked above is Andersen’s The Little Mermaid.
It was actually a bit shocking for me to realize just how often words repeat in short fiction!
I wanted to see what the survey responses from a mission/vision/values rework I am currently doing would look like with the various Voyant Tools: https://voyant-tools.org/?corpus=ef8b62446e349f2e47fdd70b04ec6e78&panels=collocatesgraph,termsberry,documentterms,summary,correlations
This text was a little short, so there aren’t as many terms to analyze as there would be in a longer text, nor did the trend analysis quite work like it would in a bigger corpus. I liked that Voyant segmented the text based on length. It was interesting to see the links and correlations between terms (again, this would be more interesting with a longer text). We’ve already made a basic word cloud with this data, but I preferred the interactive TermBerry in Voyant, as I was able to make adjustments while I looked at it.
I used this tool to explore the entirety of Bram Stoker’s Dracula [https://voyant-tools.org/?corpus=ca5e8b6213b20fb5d4a1fa04c3f9ef75]. The Voyant tool yielded results noting that the average number of words per sentence was 17.4. The most common words used were somewhat dull: “said”, “shall”, “know”, “time”, and “come”. This is still quite a useful tool! I have worked on a research project previously where the goal was to collect quantitative data such as average words per sentence of a manuscript.
https://voyant-tools.org/?corpus=4914bf22e94a693ec6b5d7ce79ef8875&panels=cirrus,reader,trends,summary,contexts
I tried out this amazing tool using Proust’s Remembrance of things past. Love the ability to track phrases and words and see the sequence. I will definitely use this in teaching my qualitative methods course as a means of helping my students see how to visualize text and how this can lead to new insights.
https://voyant-tools.org/?corpus=5ded30a3ada39bb90e74a2508d0784b9&panels=collocatesgraph,reader,trends,summary,contexts
This was a really neat activity. I analyzed Ralph Waldo Emerson’s ‘The Conduct of Life’. It would interesting if someone were to conduct research on the intersection of philosophy and bibliometrics to be able to see which core concepts were most important to philosophers in a given time period.
This was a fun tool to play around with! I used Voyant to look at The Persians by Aeschylus. The top result was “pg” because page numbers are listed. “Ch” was also among the top results. I figured out how to add pg and ch to the list of stop words so that I could get a more accurate visualization of common terms.
https://voyant-tools.org/?corpus=510015d234b15ac2195babee9d2acef7
I used voyant tools to check the frequency of pronouns she and he in English short stories
https://voyant-tools.org/?corpus=969f0fe21f76b95c78b6892f9912a66b
I was intrigued by this activity so I analyzed one of my favourite books, Alice’s Adventures in Wonderland. The results can be found here:
https://voyant-tools.org/?corpus=625d8fd474e2b46fe2f519e05078c398&panels=cirrus,reader,trends,summary,contexts
https://voyant-tools.org/?corpus=625d8fd474e2b46fe2f519e05078c398&query=said&query=alice&query=little&query=know&query=like&mode=document&view=Trends
I find it really fascinating how the results are somewhat different from my expectations! This is my first time using Voyant, I’m going to try this on some other texts now to see what results they produce…
I was intrigued by this activity so I analyzed one of my favourite books, Alice’s Adventures in Wonderland. The results can be found here:
https://voyant-tools.org/?corpus=625d8fd474e2b46fe2f519e05078c398&panels=cirrus,reader,trends,summary,contexts
https://voyant-tools.org/?corpus=625d8fd474e2b46fe2f519e05078c398&query=said&query=alice&query=little&query=know&query=like&mode=document&view=Trends
I find it really fascinating how the results are somewhat different from my expectations! This is my first time using Voyant, I’m going to try this on some other texts now to see what results they produce!
This was the first time I used a visual tool of this type. I found it extremely easy to use, even when I wanted to modify the terms to add stop words. I was curious what would be the emphasis of our institution’s OER policy, so I ran the document through the system: https://bit.ly/3gNMnSp
I added “oers” and “4.0” to the stop word list because they were the top 2 results (OER as the main concept, 4.0 from Creative Commons licensing statements on the bottom of every page). I’m encouraged to see that creative, open, and work are the top results, followed closely by commons, technology and ac (Academic Chair). These terms would express the main concepts of our policy and our intended emphasis on why we encourage OER use and opening licensing at our institution.
https://voyant-tools.org/?corpus=828ec43944693356e373f0e4adb6b596&panels=cirrus,reader,trends,summary,contexts
I looked E.M. Forsters’ A Passsage to India. This is an interesting tool that could be used for content analysis of a text, word reoccurences, etc. Even though we are using it for a literary text (great option for Digital Humanities folks) I could also see this being useful for more general research purposes, for example, a birds-eye-view of textual research data.
This tool is so powerful! I particularly like it presents the analysis in a visual format – Very intuitive!
I used it to analyze how the Times Higher Education explains its methodology for its Global Uni Rankings.
Very useful to see the data in different forms.
https://www.timeshighereducation.com/world-university-rankings/world-university-rankings-2022-methodology
I used Voyant to analyze The Island of Doctor Moreau(Wells, H. G.), it was fascinating to see how it gives so useful information about the text. particularly i wonder if this can help to figure out the difficulty level of textx as well. I wish there were similar kinf of apps for other less commonly taught languages
http://gutenberg.ca/ebooks-adelaide/wellshg-islandofdoctormoreau-adelaide/wellshg-islandofdoctormoreau-adelaide.epub
I was struck by how useful the tool would be to compare different translations of the same text, so I analyzed two translations of Ivan Turgenev’s “Father and Sons”. The novel was originally published in Russian but has various English translations. I’m interested in how translations of the same text can create variations based on the translator’s decision-making and interpretation. Even metrics as simple as vocabulary density, readability index, and average words per sentence reveal the deviations between the two translated texts.
The version translated by Charles James Hogarth had the following metrics:
Total Words: 83,938
Unique Words: 8,702
Vocabulary Density: 0.104
Readability Index: 9.814
Average Words Per Sentence: 16.0
The version translated by Constance Garnett had the following metrics:
Total words: 78,782
Unique words: 7,758
Vocabulary Density: 0.098
Readability Index: 9.463
Average Words Per Sentence: 15.4
I chose a random text in Project Gutenberg to try Voyant for the very first time and it is very simple and user-friendly, yet a powerful tool. Now I am thinking about using it with purpose and will try to analyze other texts with some hypotheses in mind.
https://voyant-tools.org/?corpus=5ea39a1dcd90fc4bfb8011281a3a67d1
For this exercise, I attempted to analyze the Federalist papers.
https://voyant-tools.org/?corpus=b7d9ff213f36ded530874151aceb6a96&panels=cirrus,reader,streamgraph,phrases,trends
It’s relatively easy to switch between the different tools – eg. streamscape, bubble lines, trends, etc. I have looked at Voyant in the past, but I never spent a lot of time in the documentation, so I have a much better understanding of what these visualizations actually do. In fact, it’s amazing how user-friendly the tool is and how quickly it analyzes the text (especially something as long as the Federalist Papers). What I’d like to understand better, is what conclusions I can derive from such visualizations. Outside of basic trends (i.e. when a phrase occurs and how frequently), I’m not clear on what I can do with this. I think this would be more self-evident when comparing two texts rather than analyzing one.
First time using this powerful tool; it is simple and user-friendly. Analysed two items; a childrens book
Book of Cats and Dogs, and Other Friends, for Little Folks –
https://voyant-tools.org/?corpus=edd764b10c485842d5e09d11d7d350a1
Mmegi Online (Botswana local newspaper)
https://voyant-tools.org/?corpus=7357a6dd845db1f0095d9a0cf903eab7
I now understand what the visualizations does. I shall use it with purpose in the future to to analyze other texts (in research).
https://voyant-tools.org/?corpus=97b0befc500178439d1b741723aa7a63&panels=cirrus,reader,trends,summary,contexts
This was my first time using Voyant and it seems like a neat tool. The top term for my resource was “https” which isn’t very helpful as I think that is just referring to whenever the document references a website. I thought the other terms, however, fairly accurately conveyed the themes and content of the book.
When doing this activity, I also thought about how/if this tool or a tool like it could be used when coming up with metadata for information resources.
I used Voyant to analyze one of the novels that I am using in my classes. I think that this tool can be quite useful as my main area of research is English literature. However, I have to wonder how much impact the paratexts that are attached to the main text have on the results–Do these extra texts skew them in any way? For example, does the license included on Project Gutenburg change the results? To get accurate results we would have to use a file that just has the text itself. I actually used Voyant to analyze two different versions of the same text– George MacDonald’s The Princess and the Goblin–and came up with slightly different results. Even though the differences are small, it could alter your conclusions.
Here are the links:
https://voyant-tools.org/?corpus=f0cbb6e7601488f676e525eb3117e87a
https://voyant-tools.org/?corpus=35a7db9001dfdee3b2288ba34eaebb34
I analyzed Act I of “The Tempest” by W. Shakespeare. Obviously, some of the most used words were characters’ names, since this is a play. It’s also interesting, I think, that verbs were also frequently used (e.g., make, hear, speak, say, hark etc.) I think this shows that the text is a dynamic piece filled with the movement of actors across the stage and interaction with each other. Voyant helped me visualize this; it’s an interesting tool.
Link: https://voyant-tools.org/?corpus=d772e9b1769ef466896ce9c6a25f66f4&view=Cirrus
This is super interesting for me as a textual scholar in Buddhist studies working on a lot of text analyses. There is a very interesting project that is called https://buddhanexus.net/ and that can overlap text passages in a really huge corpus of different Tibetan Buddhist canons and para-canonical literature.
I haven’t worked with Voyant, and it might be a little bit simple for the philological project (often in several Asian languages for which this won’t work) but it is really cool also to look at the own writing patterns!
I analyzed (of course) Siddhartha from Herbert Hesse:
https://voyant-tools.org/?corpus=ff57253efab3708a5546f3a06fcf82dd.
The most frequent words are not surprisingly siddhartha (378); govinda (141); time (139); like (137); river (110); saw (99); long (97); said (95); gutenberg (88); life (88); project (88); man (84); love (82); thought (82); learned (81).
However, it is interesting, no enlightenment, or liberation there, which would have been expected in a book about Buddhism, which shows Herman Hesse’s very free interpretation of the Buddha’s life!
I’m not familiar with Voyant and have never used it before. I performed this analysis using Vita Sackville-West’s poem The Land and was most struck by the fact that ‘man’ was the third most-used term in the poem, tied with ‘like’. I can see how this tool could be very useful for identifying the prevalence of certain words but also the absence of others.
https://voyant-tools.org/?corpus=fb54593b00d24263c3fb0be0a377a162&panels=cirrus,reader,trends,summary,contexts
For this activity I looked at Mark Twain’s Speeches and the Speeches and Letters of Abraham Lincoln, 1832-1865 (both from Project Gutenberg):
https://voyant-tools.org/?corpus=b50706474b84fe06fb136f66fb7e9360&panels=cirrus,reader,trends,summary,contexts
https://voyant-tools.org/?corpus=fde932b1f057c48ccccd41f61f239a20&panels=cirrus,reader,trends,summary,contexts
The themes of their work is very apparent in the frequent words. I’m impressed with the simplicity and accessibility of Voyant! I could see how it could be incorporated into a really engaging lesson plan. Having never used Voyant before, I found myself brainstorming ways it could be useful for different kinds of texts and thinking of analyses I’d like to try. I can see how having these applications open and available online not only supports scholars, but can stimulate new ideas and new interests just from playing around.
I have heard of this tool before, but never took the opportunity to test it out until now. I looked at analyzing Jane Austen’s Emma from the Project Gutenberg Canada website (results here: https://voyant-tools.org/?corpus=439cad371143fd3a57f13101783c6fd6&panels=cirrus,reader,trends,summary,contexts). I very much enjoyed seeing the frequency of the words used in the text and it was interesting to see “Mr.” as being the top term, followed by “Emma” and other titles which makes sense for the text. I’m interested in using this tool further and seeing the possibilities for its use.
This is a visualization of the Kaladesh playing card set for Magic: The Gathering.
This set introduced new play mechanics that utilized robots (artifacts, modules, constructs, etc.) and those that make them (artificers, artisans, etc)
https://voyant-tools.org/?corpus=da900c4c4ec9b9ef92a36b1d600c4fb4&panels=cirrus,reader,trends,summary,contexts
Wow, I did Frankenstein and the main words are chilling to some degree.
Most frequent words in the corpus: man (132); life (116); father (113); shall (107); eyes (104)
For this exercise, I chose to analyze Parasite Planet by Stanley G. Weinbaum. I was intrigued by the Corpus Phrases tool, which highlights repeating phrases in the text. Interestingly, the author chose to repeat the phrase ‘a fuzzy mass of molds’ a couple of times in the short story. I am studying mycology, and it is exciting to see words used to describe fungi in text originating from other disciplines.
Here’s the URL: https://voyant-tools.org/?corpus=04d6f6b63a4106b71c351af5078b6f7b&panels=cirrus,reader,trends,phrases,contexts
This is my first time exploring Voyant tools, and it is really interesting! I decided to see what it would do with a book on a theoretical approach I’m learning about (Activity Theory), so I uploaded several chapters of the book. https://voyant-tools.org/?corpus=af53632a02f502abceaeefeb3f0eecfa&panels=cirrus,reader,trends,summary,contexts
The book citation is:
Engeström, Y. (2014). Learning by Expanding: An Activity-Theoretical Approach to Developmental Research (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9781139814744
I definitely have a lot to learn about Voyant, but I appreciated how the word cloud (Cirrus) helped me see some frequently used terms, and by clicking on a specific term in the cloud I could then see where it was used in context in the “reader” tool. It was interesting to see word frequency graphed as well in the “trends” tool. I’m still exploring some of the other tools available – it seems you might be able to ‘code’ data through the creation of “categories” – though I notice this is a new experimental feature and the developers warn: “expect things to go wrong”. (Doesn’t instill confidence, ha ha).
Still, I think Voyant could be very powerful for analysis of interview data, for example – particularly if you had many interviews / multiple participants.
This was my first time using Voyant, and I uploaded a .txt file of ~300 job postings, thinking it could be interesting to see:
https://voyant-tools.org/tool/Cirrus/?stopList=keywords-5dfb4541ecc3f0814308fa34da97ec73&whiteList=&visible=45&corpus=e202acf4ac091b375acef3a0556badca
It seems like a very powerful browser-based tool. One thing though that I was struggling with is that a lot of the terms that are most common are stop words (“a”, “the”, etc.). I noticed in the documentation that there is an option to add your own stopwords, and so I chose the English stopwords. However, I got an error message “Transaction aborted: This tool has exceeded the maximum run time and has returned partial results.”. I tried creating a custom stopwords list, but it too timed out.
https://voyant-tools.org/docs/#!/guide/stopwords
Custom stopwords list:
a
and
as
be
for
in
is
of
on
or
that
I used Voyant on a small portion of the script for Chernobyl as I was curious as to what words would be used for when writing for the show. Most frequent words used was: reactor (3); wind (2); water (2); vehicles (2); valves (2) and this makes sense as the text that was analyzed from from the first episode, so I can see that these words can help me easily visualize and describe the environment. Also found it interesting that you can click on the words and it would show you frequencies which can be great for keeping track how often words are used and to think about why certain words and being used more than others. https://voyant-tools.org/?corpus=ede6649ee8c4443bcedc0376c7a7aac5&view=Cirrus
This was my first time using Voyant – it’s a neat tool! I had it analyze C.S. Lewis’ The Lion, the Witch, and the Wardrobe, which can be seen here: https://voyant-tools.org/?panels=cirrus%2Creader%2Ctrends%2Cphrases%2Ccontexts&corpus=d93bb200126d77ff307466318e292011
I really like that you can see both most frequent words and phrases using Voyant. I had a lot of fun looking at the most used phrases for a few different books available from Project Gutenberg Canada – some of the phrases can give you a great sense of the author’s style of writing, which you don’t necessarily get from the most frequently used words.
https://voyant-tools.org/?corpus=625d8fd474e2b46fe2f519e05078c398&panels=cirrus,reader,trends,summary,correlations
I used Voyant to analyze Lewis Carroll’s “Alice’s Adventures in Wonderland”, one of my favourite novels. It was interesting seeing the novel broken down into most common words and phrases; who knew that the word “Alice” was used over 400 times! For my own academic purposes, I could see this program being useful for double-checking that I’m not over-using particular words or phrases in a paper.