- Jul 2022
-
lacol.sites.haverford.edu lacol.sites.haverford.edu
-
Adversely, the Topics feature did not seem super helpful which was surprising because I initially thought that this feature would be helpful, but it just did not seem super relevant or accurate. Maybe this is because as a work of literature, the themes of the play are much more symbolic and figurative than the literal words that the play uses. Perhaps this function would work better for text that is more nonfiction based, or at least more literal.
I read your Voyant analysis of Henrik Ibsen's "A Doll's House," and I think we almost pick the same tools that we believe to be crucial for our text analysis. Like you, I mostly visualize my chosen literary work with Cirrus, Terms, Berry, and Trends. I also use links to ?look into how these words are used interdependently to contextualize the story told. I also had difficulty understanding how functions like Topics would benefit my understanding of the texts on a layered and complex level. I checked and thought maybe the problem was with the word count of the document. By default setting, Topics generates the first 1000 words in a document, and A Doll's House has 26210 words. In order to use this tool in the most efficient way possible, you can try to use the Topics slider ( the scroll bar) to adjust the number of topics you want to generate (max is 200). I have read A Doll's House before, so I couldn't speak for those who haven't. However, the clusters of chosen terms hint to me that this fiction deals with bureaucracy and finance via repeated words like "works," "money," and "paper." I can also recognize some words classified as names, so many characters are involved in the story. There is also a vague clue of the story's setting, which is during the winter season, from the repetition of the word "Christmas." It appears that someone is getting angry at someone for their wrongdoings, and this drama occurs in a family. While Topics cannot give me a complete storyline, it gives me a good chunk of puzzles to piece together the core gist of the story. It happened to me when I analyzed Herman Melville's Moby Dick. Words like "whale," "sea," "sailor," and "chase" allowed me to make a reasonable assumption that there was a group of sailors that went after a giant whale in the sea. I still prefer to use other tools, but that was how I utilized Topics for my knowledge of the text. I agree that text with more literal content, like self-help books, would definitely yield better results with Voyant Tools' Topics.
-
- Jun 2022
-
dlsanthology.mla.hcommons.org dlsanthology.mla.hcommons.org
-
Thus flexibility is an important virtue in computer-assisted textual analysis, and testing a project on a subset of texts or methods can avoid wasted effort.
Flexibility has almost become a sought-after characteristics of any projects ever conducted in this world, let alone those that belong to the school of humanities. Any individual or group entering a long-term project should be aware that predicting the outcome of the project is never a part of their project. It's impossible to identify and avoid surprise factors on a long road, but it's definitely possible to have an open mindset that's ready fpr any difficulty coming along the way and for brainstorming solutions that resolve this "shock". In many cases, these unexpected variables are what that renders the project memorable and special and sustainable and valid and reliable. In many cases, changing the initial direction of the project when faced with these unforeseen elements are for the better and produce even better results. Testing out different methods on textual analysis is a particularly great advice for those who are bound to carry a project in the coming future.
-
- Mar 2022
-
only-the-questions.glitch.me only-the-questions.glitch.me
-
https://only-the-questions.glitch.me/
A tool for extracting all the questions out of a particular text.
Via: https://uxdesign.cc/the-power-of-seeing-only-the-questions-in-a-piece-of-writing-8f486d2c6d7d
Link to [[searching for questions while reading]]
-
- May 2021
- Jan 2021
-
theconversation.com theconversation.com
-
In addition, a recent study analyzed 10,000 words from Trump’s and President-elect Joe Biden’s campaign speeches. It concluded – perhaps surprisingly – that Trump and Biden’s language was similar. Both men used ample emotional language – the kind that aims to persuade people to vote – at roughly the same rates. They also used comparable rates of positive language, as well as language related to trust, anticipation and surprise. One possible reason for this could be the audience, and the persuasive and evocative nature of campaign speeches themselves, rather than individual differences between speakers.
-