ThingLink: The Digital Image/Video Annotation Tool

By Mary Mackoy

What is this Thinglink…thing?

ThingLink is an online image and video annotation tool. Using ThingLink you can add annotations directly to images and videos. For example:  I analyzed the poster for Star Wars: The Last Jedi. Instead of flipping back and forth between my analysis and the picture you can read specific annotations directly connected to the element being analyzed.

Reiner, Andrew. “Highlights from The Star Wars: The Last Jedi Livestream.” Game Informer. 14 Apr 2017. Web. 11 May 2017.

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Sentiment Mining

By Emily Snyder



Sentiment mining is pretty much a fancy way to say emotion tracker; simple, right?
With sentiment mining, we can determine certain emotions within a text based on how frequent they’re used while also showing where in the text positive and negative emotions appear most; which is not so simple.

Sentiment mining is pretty cool but, you have to keep in mind that as of right now, there are only eight emotions that are recognizable with sentiment mining. To see how they determined whether an emotion is positive or negative, visit the NCR Word-Emotion Association Lexicon.

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Topic Modeling

By Clint Hammerberg

Topic modeling is a powerful technique that looks for recurring clumps of words using co-location and tracks them through a larger body of text, which can be an large single work of a collection of other texts. This allows for a researcher to identify potential topics that are prevalent. The number of topics depends on how many you want to produce.

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By Ashle’ Tate

What is clustering?

If you’re anything like me, a teacher candidate and a huge foodie, when you hear the word ‘cluster’ the first thing you think of are those delicious chocolates with caramel and nuts.The second thing you think of is the grouping and instructional practice that supports gifted and talented students…. Well I’m here to tell you that clustering in the world of DH is neither of those things.

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By: Kelsea Altheim

How: In order to classify texts to one another, it is necessary to have a large amount of texts available to analyze; therefore, our professor, Dr. Jaime Jordan, compiled a corpus of different texts ranging from the Victorian era to the modern era for our class to use. Then, using R and R Studio, we tidied the data up and in the end were able to create the classifications that you see in the examples above.

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