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The Single Most Common Language Technology Mistake (and how to avoid it)

This is an excerpt from my book “The 9 Most Common Language Technology Mistakes (and how to avoid them!)”. If you’d like to grab a copy (plus a handy checklist) you can get it on my Ko-fi. If you’d prefer a video version of the same information, you can check out the livestream I did here. The single most common mistake I see language technologists make, especially newer ones, is failing to…

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Large language models cannot replace mental health professionals

I recently posted on Twitter the strong recommendation that individuals do not attempt to use large language models (like BERT or GPT-3) to replace the services of mental health professionals. I’m writing this blog post to specifically address individuals who think that this is a good idea. CW: discussions of mental illness, medical abuse, self-harm and suicide. If you are in the US and…

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The trouble with sentiment analysis

Two things spurred me to write this post. First, I’d given the same advice three times which, according to David Robinson‘s rule, meant it was time. And, second, this news story on a startup that claims that they can detect student emotions over Zoom. With those things in mind, here is my very simple guidance on sentiment analysis: You should almost never do sentiment analysis. A picture of a…

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An emoji dance notation system for TikTok dance tutorials 👀💃

This blog post is more of a quick record of my thoughts than a full in-depth analysis, because when I saw this I immediately wanted to start writing about it. Basically, TikTok is a social media app for short form video (RIP Vine, forever in our hearts) and one of the most popular genres of content is short dances; you may already be familiar with the concept. HOWEVER, what’s particularly…

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#language #linguistics #syntax

Who all studies language? 🤔 A brief disciplinary tour

Buckle up friends, we’re going on a tour! One of the nice things about human language is that no matter what your question about it might be, someone, somewhere has almost certainly already asked the same thing… and probably found at least part of an answer! The downside of this wealth of knowledge is that, even if you restrict yourself to just looking at the Western academic tradition, 1)…

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What you can, can’t and shouldn’t do with social media data

Earlier this summer, I gave a talk on the promise & pitfalls of social media data for the Joint Statistical Meetings. While I don’t think there’s a recording of the talk, enough people asked for one that I figured it would be worth putting together a blog post version of the talk. Enjoy!

What you can do with social media data

Let’s start with the good news: research using social media data has…

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#data science #ethics #linguistics #lingustics #NLP #research #social media #technology #twitter

Are emoji sequences as informative as text?

Something I’ve been thinking about a lot lately is how much information we really convey with emoji. I was recently at the 1st International Workshop on Emoji Understanding and Applications in Social Media and one theme that stood out to me from the papers was that emoji tend to be used more to communicate social meaning (things like tone and when a conversation is over) than semantics (content…

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#data science #data viz #emoji #internet #internet linguistics #linguistics #NLP #science #technology

Are emoji sequences as informative as text?

Something I’ve been thinking about a lot lately is how much information we really convey with emoji. I was recently at the 1st International Workshop on Emoji Understanding and Applications in Social Media and one theme that stood out to me from the papers was that emoji tend to be used more to communicate social meaning (things like tone and when a conversation is over) than semantics (content…

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#data science #data viz #emoji #internet #internet linguistics #linguistics #NLP #science #technology

Datasets for data cleaning practice

Looking for datasets to practice data cleaning or preprocessing on? Look no further!

Each of these datasets needs a little bit of TLC before it’s ready for different analysis techniques. For each dataset, I’ve included a link to where you can access it, a brief description of what’s in it, and an “issues” section describing what needs to be done or fixed in order for it to fit easily into a data…

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How do we use emoji?

Those of you who know me may know that I’m a big fan of emoji. I’m also a big fan of linguistics and NLP, so, naturally, I’m very curious about the linguistic roles of emoji. Since I figured some of you might also be curious, I’ve pulled together a discussion of some of the very seriousscholarly research on emoji. In particular, I’m going to talk about five recent papers that explore the exact…

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#characters #emoji #internet #internet linguistics #linguistics #technology #twitter

Parity in Utility: One way to think about fairness in machine learning tools

First, a confession: part of the reason I’m writing this blog post today is becuase I’m having major FOMO on account of having missed #FAT2018, the first annual Conference on Fairness, Accountability, and Transparency. (You can get the proceedings online here, though!) I have been seeing a lot of tweets & good discussion around the conference and it’s gotten me thinking again about something I’ve…

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#ethics #fairness #fatml #machine learning #technology

A Field Guide to Character Encodings

I recently gave a talk at PyCascades (a regional Python language conference) on character encodings and I thought it would be nice to put together a little primer on a couple different important character encodings.

So many characters, so little time.

If you’re unfamiliar with character encodings, they’re just a variety of different systems used to map a string of binary (i.e. 1’s and 0’s) to a…

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How to be wrong: Measuring error in machine learning models

One thing I remember very clearly from writing my dissertation is how confused I initially was about which particular methods I could use to evaluate how often my models were correct or wrong. (A big part of my research was comparing human errors with errors from various machine learning models.) With that in mind, I thought it might be handy to put together a very quick equation-free primer of…

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#classification #error analysis #machine learning #regression #statistics

Data science & kitchen gadgets

One of the things I really enjoy about my current job is chatting with other data science folks. Almost inevitably in the course of these conversations, the old “Python vs. R” debate comes up.

For those of you who aren’t familiar, Python and R are both programming languages often used by data scientists and other folks who work with data. Python is a general-purpose programming language…

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normalshrimp

a 1929 Fleischer Studios mouth chart.

bighugefrog

this is horrifying and i love it

Analyzing Multilingual Data

This blog post is a little different from my usual stuff. It’s based on a talk I gave yesterday at the first annual Data Institute Conference. As a result, it’s aimed at a slightly more technical audience than my usual stuff, but I hope I’ve done an ok job keeping it accessible. Feel free to drop me a comment if you have any questions or found anything confusing and I’ll be sure to help you out.…

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leftoversalad

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