#56: Why we lol

💎 Word gems

Why We Use “lol” So Much (Vice / Shayla Love)

It’s obvious lol doesn’t really mean laugh out loud anymore, but I often wonder if I use it too much lol. This article defines it as a discourse marker (like saying “well”) and explores what that means.

I rarely go a few texts or Slack messages without dropping in an lol. Some sentences feel like they need a lol at the beginning or end to communicate the tone I’m trying to convey, or seem harsh or grating without an lol. I sometimes have to actively stop myself from adding lol to too many phrases. Because lol so regularly graces the end of our sentences, it’s been said that lol has morphed into a kind of punctuation mark—but it’s actually much more than that. Lol has assumed a remarkably expansive linguistic role through the ways we use it in our daily communication.

Inside Spotify’s Recommender System: A Complete Guide to Spotify Recommendation Algorithms (Music Tomorrow / Dmitry Pastukhov)

If you’ve ever wondered how recommendation algorithms break down content and find similar things, this one about Spotify is for you.

Spotify generates at least three perceptual, high-level features designed to reflect how the track sounds like in a more holistic way:

1. Danceability, describing how suitable a track is for dancing based on a combination of musical elements, including tempo, rhythm stability, beat strength, and overall regularity.

2. Energy, representing "a perceptual measure of intensity and activity", based on the track's dynamic range, perceived loudness, timbre, onset rate, and general entropy.

3. Valence, describing "the musical positiveness of the track". Generally speaking, tracks with high valence sound more positive (e.g., happy, cheerful, euphoric), while songs with low valence sound more negative (e.g., sad, depressed, angry)

It's a Golden Age for Armchair Generals (Vice / Matthew Gault)

One of my biggest gripes with the web is that there are too many opinions (yes, I’m well aware of the irony). The quantity of information has made quality or expertise indistinguishable from garbage and the Russian invasion of Ukraine is a an excellent backdrop to expose this absurdity.

There’s more information, both good and bad, than ever before. But the onus to sort through it is on the viewer. This becomes extremely hard during a war. The stakes are literally life and death, and all sides are willing to lie to score propaganda victories. In the unsorted mess of the Twitter timeline, a reply about mud from a guy cosplaying as Eisenhower online can move to the top of your feed as easily as a serious OSINT analyst who spent hours verifying the movements of tank columns in the country using satellite imagery.

💩 Cool shit

Ledger of Harms - We don’t talk about the harms of tech enough. This is a fantastic list that documents those harms, with supporting evidence.

A Good Movie To Watch - If, like me, you’re often struggling to pick what to watch, check this out. It seems to be a fairly helpful recommendation tool.

Ukraine Maps - I’m weary of sharing maps of war because it’s often difficult to know how reliable the information is. Nevertheless, the NY Times’ use of data maps is an interesting look at how an unfolding crisis is reported.

Framed - Another Wordle-like game. This time, guess the movie based on its stills.

Tarot Reader - Look past the interface to a fun little example of digitizing tarot card reading.

Driving Simulator on Google Maps - Drive on top of Google Maps.

Plain Text Sports - Sports scores in the most basic, text-only website.

Building games and apps entirely through natural language using OpenAI’s code-davinci model - This is an utterly fascinating article that explores, with demos, how OpenAI can generate code based on natural language.

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