Calling something a ‘fad’ has many of the same problems as calling something a ‘bubble’. It’s an invitation to selective reasoning. As Sumner likes to point out, most of the things which get called a ‘bubble’ never turn out to be that, it was just an insult and then a bunch of cherrypicked examples and flexible reasoning (think of all the people who called Bitcoin a bubble when it collapsed to a price far higher than when they called it a bubble).
I think you could get something more useful from a more neutral formulation, like specific cultural artifacts. So 2 recent relevant papers which come to mind would be https://www.nature.com/articles/s41467-019-09311-whttp://barabasi.com/f/995.pdf . You could do a post hoc analysis and operationalize ‘fad’ as anything which rose and fell with a sufficiently steep average slope. (Obviously, anything which rises rapidly and then never decays, or only slowly decays, doesn’t match what anyone would think of as a ‘fad’, or rises slowly and decays slowly etc.)
Ah, yeah model building from past fads would be useful. I am mostly interested in tracking things like current trends in a mostly content agnostic way, i.e. what is currently being shared the most across lots of platforms. Probably this is a paid service by some marketing firms.
How would you define ‘fad’ in an objective and non-pejorative way?
Something currently undergoing the steep part of its sigmoid wrt memetic replication maybe.
Calling something a ‘fad’ has many of the same problems as calling something a ‘bubble’. It’s an invitation to selective reasoning. As Sumner likes to point out, most of the things which get called a ‘bubble’ never turn out to be that, it was just an insult and then a bunch of cherrypicked examples and flexible reasoning (think of all the people who called Bitcoin a bubble when it collapsed to a price far higher than when they called it a bubble).
I think you could get something more useful from a more neutral formulation, like specific cultural artifacts. So 2 recent relevant papers which come to mind would be https://www.nature.com/articles/s41467-019-09311-w http://barabasi.com/f/995.pdf . You could do a post hoc analysis and operationalize ‘fad’ as anything which rose and fell with a sufficiently steep average slope. (Obviously, anything which rises rapidly and then never decays, or only slowly decays, doesn’t match what anyone would think of as a ‘fad’, or rises slowly and decays slowly etc.)
Ah, yeah model building from past fads would be useful. I am mostly interested in tracking things like current trends in a mostly content agnostic way, i.e. what is currently being shared the most across lots of platforms. Probably this is a paid service by some marketing firms.