- 🚨 Eyeo 2014 Ignite - Sarah Groff-Palermo
- 🍿 The Secret Life of Pronouns: James Pennebaker at TEDxAustin
- 🍿 Overview of Word Counting + Text Analysis
- 🚨 Associative Arrays in JavaScript
- 🚨 Word Counting (in 3 parts!)
- 💻 Additional p5.js word counting visualization
- 💻 p5.js word counting two documents visualization
- transformers.js Tokenizer playground
- OpenAI Tokenizer
split()+ regex- RiTa.js tokenize() function
- 🔗 SPEECH COMPARISON by Rune Madsen
- 🔗 Word Tree by Martin Wattenberg and Fernanda Viegas
- 🔗 Writing Without Words by Stephanie Posavec
- 🔗 Annual Report 2013 by Nicholas Feltron
- 🔗 Literary Constellations by Nicholas Rougeux
- 🔗 An Interactive Visualization of Every Line in Hamilton by Shirley Wu
- 🔗 Book-Book by Sarah Groff-Palermo I can't find this project active online anymore!
- 🔗 Partisan Thesauras by Melanie Hoff no longer working
- 🍿 TF-IDF Video Tutorial
- 💻 TF-IDF sketch updated for p5.js 2 🍿- 🍿 Logarithmic scale | Logarithms by Khan Academy
- 🔗 TF-IDF
- 📚 A Plan for Spam by Paul Graham
- 🍿 Explaining Bayesian Problems Using Visualizations by Luana Micallef
- 🍿 Bayes theorem, the geometry of changing beliefs
- 💻 Sample start of Bayesian Classification Library
Part of the challenge of understanding algorithmic oppression is to understand that mathematical formulations to drive automated decisions are made by human beings. While we often think of terms such as “big data” and “algorithms” as being benign, neutral, or objective, they are anything but.
- 📕 Algorithms of Oppression: How Search Engines Reinforce Racism, Chapter 1: A Society Searching, by Safiya Umoja Noble
1: In preparation for next week, add a link to a data source or API (even just data that appears in raw form on a web page) that interests you! Don't worry about this too much, anything will do! I'll use this list to prepare examples for next week.
2: Choose a text or data source and count word frequencies following the examples above. Design your own creative output. This need not be visual (sonify word counts?) nor does it require code (knit your own word frequency scarf!). Some things to consider:
- Use a language other than English!
- What happens if you compare different texts according to word frequency?
- Can you look at frequency of how words appear next to each other?
Reflect on your process of word counting and consider the following questions (drawing connections to Safiya Umoja Noble’s Algorithms of Oppression, Chapter 1):
- Did you discover anything new about the text by counting words?
- What is lost from word counting?
- Challenge the assumption that algorithms for analyzing text (such as word counting or search engine rankings, as Noble shows) are neutral.
- Name - Data Source
- Ivy - 2018 Central Park Squirrel Census - Squirrel Data
- Olivia - Iliad
- Sky - Weather API_Open Meteo
- Fiona - Open Food Facts, sample query
- DJ - Guardian Open Platform API, SEMrush API, Reddit API, X API v2
- Billy - Fragrance Finder API, Fragrance Data API
- Junqi - NYCopendata-Evictions
- Niki - The Cat API
(Please note you are welcome to post under a pseudonym and/or password protect your published assignment. For NYU blogs, privacy options are covered in the NYU Wordpress Knowledge Base. Finally, if you prefer not to post your assignment at all here, you may email the submission.)
- Name - what is the title of your assignment?
- Ivy - Chinese Character Counting
- Sky - Most Frequent Words in Korea & U.S. Constitution
- DJ - Spiral Word Count Visualizer
- Fiona - Word Counting for 7 Days Meal Plan
- Billy - The only Indonesian text you'll read here
- Xueyu - Word Counting with tones
- Junqi - Sloppy Summary
- Haya - Frantic Words
- Duban - Comparing Bauhaus and Speculative Design Language
- Niki - Word Counts in Canto pop Lyrics
- Bairui - Word Counting Tutorial by Recho
- Rachel - CAPS
- Olivia - cursedVisions
- Ping - Word Frequency: Little Red Riding Hood
- 🚨 Watch this video tutorial! (this is technical info needed for the examples). Of course if you alreaddy know this material, you can skip.
- 🔢 This is found in a group, maybe pick just one to check out!
- 🍿 Additional video if you have a particular interest and want to do a deeper dive.
- 📕 Required reading! Let's make sure we all have read this.
- 📚 Optional additional reading for a deeper dive.
- 💻 Code examples here!
- 🔗 Extra reference material / link