The world modelA composite, not a person
Mateo
21Buenos Aires
Engineering student
Heavy consumption, no public footprint, and the highest rate of onward sharing in the set. Almost all of it unobservable.
At a glance
Online
- Between lectures
- After midnight
Where
- TikTok because the ten minutes between lectures fit three videos.
- YouTube because long tutorials at night, at one and a half speed.
In the field
Reads, never postsLate night
The day
Mateo watches more than anyone else here and posts less than almost anyone. His feed is a private utility: ten minutes between lectures, then long technical videos after midnight at one and a half speed.
What he does instead of posting is forward. Six friends, one group chat, several times a day. He is the reason things travel, and none of that travel appears in any public metric.
Field notes
What is observable about this kind of audience, and the published work that describes it.
01Participation inequality is the norm
In most online communities a small minority produces nearly all visible contribution while the large majority only reads. Estimates cluster around one percent creating and nine percent responding (Nielsen, 2006; van Mierlo, 2014). The visible commenters are the exception, not the sample.
02Format preference is situational
He wants ten seconds at midday and forty minutes at midnight. Preference of this kind belongs to the occasion rather than to the person, which is why demographic segmentation predicts it poorly.
03Attention and budget are different currencies
He has a great deal of the first and very little of the second. Treating them as interchangeable overvalues him this year and undervalues him over a decade.
Who sits nearby
Nearness in the field is behavioural, not geographic. The unnamed individuals around a reference persona are people whose observable behaviour resembles theirs.
References
- Nielsen, J. (2006). The 90-9-1 Rule for Participation Inequality in Social Media and Online Communities. Nielsen Norman Group.
- van Mierlo, T. (2014). The 1% Rule in Four Digital Health Social Networks: An Observational Study. Journal of Medical Internet Research, 16(2).