Category Archives: words

25Apr / 2023

Words used in cannabis business names

Daniel Wolfe for The Washington Post looked at the similar word choices across cannabis business names:

To check if companies are distinguishing themselves, we analyzed every dispensary listing from WeedMaps, a map directory for local cannabis distributors. Here’s what patterns emerged when we examine the company’s name through a language model.

The premise is that businesses should aim for brand differentiation, and if all the dispensaries have similar names, it’s tough for any one to stand out.

I guess that’s true, but all I could think about was all the Chinese restaurants that I’ve been to, which also have similar names, even in the same city. People definitely are still able to pick out the good places.

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Posted by in business, Cannabis, Statistical Visualization, Washington Post, words

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14Jun / 2022

Different languages, but similar information rates

Christophe Coupé and company analyzed speech rate (on the left) across different languages, and then compared it to information rate (on the right) in bits per second. While speech rate and information rate are still coupled, there’s less variation in information rate across languages. More syllables doesn’t necessarily mean more information.

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Posted by in information, language, Statistical Visualization, words

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06Jul / 2021

Find a color palette based on words

PhotoChrome is a straightforward tool that lets you use search terms to find a color palette. Just enter a query, and it spits out a color scheme of hex values based on matching images.

It’s like Picular from a few years ago but more focused with a copy-paste.

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Posted by in apps, color, Images, words

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04Feb / 2021

✚ Uncertain Words and Uncertain Visualization, Better Together

People's interpretation of a chart can change if you use differents words to describe it, even if the data stays the same. Read More

Posted by in annotation, The Process, uncertainty, words

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17Jul / 2020

Words used to describe men and women’s bodies in literature

Authors tend to focus on different body parts for men and women, and the descriptions used for each body part also vary. For The Pudding, Erin Davis parsed a couple thousand books to see the scale of the skews.

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Posted by in Body, Erin Davis, gender, Infographics, Liana Sposto, literature, Pudding, words

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19May / 2020

Machine learning to make a dictionary of words that do not exist

Thomas Dimson trained a model to generate words that don’t exist in real life and definitions for said imaginary words. If you didn’t tell me the words were machine-generated, I’d believe a lot of them were actual parts of the English dictionary.

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Posted by in machine learning, statistics, Thomas Dimson, words

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20Mar / 2020

Wheel of emotional words, in case you’re having trouble finding the words these days

You’re probably feeling a range of emotions these days. It helps if you can express them. This emotional word wheel by Geoffrey Roberts might help:

I work with people who have limited emotional vocabulary and as a result the intensity of their negative emotions and experiences is heightened because they can’t describe their feelings (especially their negative feelings). That’s why this list is heavily focused on negative emotions/ experiences. Being able to clearly identify how we are feeling has been shown to reduce this intensity of experience because it re-engages our rational mind.

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Posted by in emotion, Geoffrey Roberts, Infographics, words

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09Oct / 2018

Measuring the varied sentiments of good and bad words

There was a survey a while back that asked people to provide a 0 to 100 percent value to probabilistic words like “usually” and “likely”. YouGov did something similar for words describing good and bad sentiments.

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Posted by in sentiment, Statistical Visualization, words

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06Jul / 2018

How people interpret probability through words

In the early 1990s, the CIA published internal survey results for how people within the organization interpreted probabilistic words such as “probable” and “little chance”. Participants were asked to attach a probability percentage to the words. Andrew Mauboussin and Michael J. Mauboussinran ran a public survey more recently to see how people interpret the words now.

The main point, like in the CIA poll, was that words matter. Some words like “usually” and “probably” are vague, whereas “always” and “never” are more certain.

I wonder what results would look like if instead of showing a word and asking probability, you flipped it around. Show probability and then ask people for a word to describe. I’d like to see that spectrum.

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Posted by in statistics, uncertainity, words

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21Jun / 2018

History of the word ‘data’

Sandra Rendgen describes the history of “data” the word and where it stands in present day.

All through the evolution of statistics through the 19th century, data was generated by humans, and the scientific methodology of measuring and recording data had been a constant topic of debate. This is not trivial, as the question of how data is generated also answers the question of whether and how it is capable of delivering a “true” (or at least “approximated”) representation of reality. The notion that data begins to exist when it is recorded by the machine completely obscures the role that human decisions play in its creation. Who decided which data to record, who programmed the cookie, who built the sensor? And more broadly – what is the specific relationship of any digital data set to reality?

Oh, so there’s more to it than just singular versus plural. Imagine that.

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Posted by in data, history, statistics, words

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