Despite what you may have heard, the Okcupid blog post, "Your Looks and Your Inbox," does show a substantial messaging premium for attractive males (Rudder, 2009)

Since bluepill advocates seem to be fixated on Okcupid's blog post on attractiveness and messaging rates, a more disciplined look at the content is well overdue.

First, I'll start with what is arguably the most abused portions of the blog post: the messaging and attractiveness density histograms:

for male messaging: https://cdn-images-1.medium.com/max/800/0*aiEOj6bJOf5mZX_z.png

and for female messaging: https://cdn-images-1.medium.com/max/800/0*aWz0dYzuUR7PO3dP.png

These images are often disembodied from the rest of the blog content and spewed across reddit as "atomic bluepill" failevidence to counter redpill and blackpill claims.

The problem is the blog post clearly states this about the density histograms:

The information I’ll present in this post is not normalized

This is crucial to interpreting the histograms. It's clear the messaging plots are simply showing the total number of messages received by each looks rating as a proportion (%) of the total number of messages sent out on their platform, but because no normalization was performed, the messaging data is raw and uncorrected for the number of individuals at each rating level. 100 messages going to 100 different individuals is much different than 100 messages going to 10, but you can't even infer that level of granularity with the data (no absolute numbers provided).

Thankfully, the blog author did include a more interpretable graph, and here it is:

https://cdn-images-1.medium.com/max/800/0*rRhMB4YoU-HURGeE.png

Sure, the female recipient graph is exponential while the male recipient graph looks cubic, but note the scale is in multipliers and, unfortunately, absolute numbers were not given anywhere in the blog post. It is almost certain (based on, for instance, Hitsch 2006 and 2010) that there is at least an order of magnitude more messages being received by female recipients than male recipients, such that the gender-controlled multipliers conceal the likely massive disparity that is present even at the lower end of the attractiveness spectrum where the two trend lines appear to converge.

It should also be pointed out that the messaging best fit trend line for male recipients is similar to what Hitsch 2006 described before binning out men in the top 5% of looks. Hence, it is entirely possible that the data -- as a consequence of how final attractiveness scores were assigned and how the data was binned -- obscures a winner-takes-all "superstar effect" Hitsch and colleagues identified in their dataset.

The Okcupid blog concludes by showcasing the reply rates data, which is consistent with expected trends.

tl;dr: Overall, the entire blog post is consistent with the well-supported observation that attractiveness is the most robust predictor of initial romantic interest.