Laughter is complex. In real life it can be hard to tell the real from the fake. Online, it is even harder, with fewer visual cues and a wider range of tools to express laughter. As internet language develops, new forms of laughter spread like a cold in a classroom. This is a three-part series that takes a closer look at the usage, evolution, and perception of the digital laugh.
11/04/2019How funny is it?
As with most lingo, the intent and perception of each laugh varies from person to person. Help us do some casual science to get a sense of how you use some of the most common laughs compared to other internet people.
Pick a laugh. Not familiar? Skip it!
Tell us how funny something really is when you use
- Unamused, not smiling; perhaps even feeling spiteful.
- Neutral. Used as filler or to be nice. No physical response.
- A single breath of air exits the mouth, a possible smile forms.
- Visibly amused. Puffs of air released, slight body gyration.
- Laughing so much that breathing is hard; actually rofl-ing.
10/31/2019The evolution of lol
Today, lol is prodigious. It can be found once every 54 comments on Reddit. But has that always been the case? We went back 10 years (for reference: Obama’s first year in office) to find out. Here is the rise of lol in one chart.
Lol is increasingly used for more than “laughing out loud.” According to McCulloch, it can soften confrontation, request sympathy, or add subtle layers of meaning. You might find it unfair to compare lol to “real” laughter, but as Mculloch points out,
in some ways, lol hasn’t changed its meaning so very far from its roots in laughter. Sure, sometimes we laugh at a direct joke, something we can point at and say, ‘That’s funny.’ But there’s also nervous laughter, social laughter, and polite smiles.
Lol’s transformation is less like a shift and more like an evolution. Squirtle became Blastoise. A butter knife became a Swiss Army knife. Dancing 90’s J Lo became triple-threat J Lo? J Lol.
This story was published in October 2019. Questions or comments? email@example.com.
Data and Method
We used BigQuery to process every Reddit comment since 2009. This isn’t a comprehensive survey of every single laugh, but darn close. We analyzed way more laughs than displayed but only include results with 0.01% or greater share of laughs. We accounted for all sorts of laughter misspellings and variations with some handy regex patterns. Sadly, this does not include emojis which are certainly a big player in today’s laugh arsenal. We also didn’t include true keyboard smashing, a favorite with the kids. Punctuation was ignored so we didn’t examine exclamation points as a laugh enhancer.