Mel Andrews

@bayesianboy · Philadelphia · joined 14 May 2019

I’m not like the other Bayesians. I’m different. Thinks about philosophy of science, AI ethics, machine learning, models, & metascience. postdoc @ Princeton.

32 254Followers

8 615Following

1 001Posts total

53.2KViews on collected posts

Posts recentes

Mel Andrews@bayesianboy18 Sep

First submit of the term, let me know if you want to talk data models (or read a draft!). https://t.co/qZE4MMI10c

2.6K views · 51 likes · 0 reposts · 0 replies Open on X →

Mel Andrews@bayesianboy17 Sep

“Who wants to see the new Love Island?” Quiet babe my favorite show is on: https://t.co/GCyIAg7pvS

1.7K views · 22 likes · 0 reposts · 1 replies Open on X →

Mel Andrews@bayesianboy15 Sep

……In perfectly unrelated news, have an advert……. https://t.co/TB0d7IbYA3

1.5K views · 14 likes · 1 reposts · 0 replies Open on X →

Mel Andrews@bayesianboy14 Sep

A.I. Slopware Is Everywhere Now. Nobody Is Using It. https://t.co/Onh2jYveYF 1.9K views · 4 likes · 2 reposts · 0 replies Open on X →

Mel Andrews@bayesianboy12 Sep

Do I have any friends out there in forensic accounting? 1.4K views · 5 likes · 0 reposts · 1 replies Open on X →

Mel Andrews@bayesianboy11 Feb

@bayesianboy Useful. TY. Missing, I think, are 1) the role of doubt in science and 2) the role of metadata. 1)✔️that analysis is theory-laden, but I think we often deny one or more parts of a theory to see how the most natural analysis changes as a result. We might have very diff 304 views · 0 likes · 0 reposts · 1 replies Open on X →

Mel Andrews@bayesianboy2 Oct 2025

@bayesianboy @hybrid 671 views · 2 likes · 0 reposts · 0 replies Open on X →

Mel Andrews@bayesianboy25 Sep 2025

My article on AI for science, in which I characterize a deviant notion of scientific objectivity rooted in the impossible ideal of theory-free inference, is available now open-access in Erkenntnis https://t.co/zRfOyOdFZy 43.2K views · 276 likes · 49 reposts · 5 replies Open on X →

Em comparação com contas do mesmo porte

5 posts dos últimos 90 dias, ao lado da faixa de 10K–100K seguidores. aparece para muita gente, mas poucos desses espectadores reagem.

Mediana de visualizações1 711esta conta924mediana para 10K–100K

Alcance, %5.30%esta conta3.62%mediana para 10K–100K

Engajamento, %1.01%esta conta1.52%mediana para 10K–100K

Métrica	Esta conta	Mediana para 10K–100K	Proporção
Mediana de visualizações por post	1 711	924	1.85×
Alcance (visualizações ÷ seguidores)	5.30%	3.62%	1.47×
Taxa de engajamento	1.01%	1.52%	0.66×

Outras contas desta faixa → Comparar com outra conta → Como estas referências são construídas →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

43.2K25 Sep

6712 Oct

30411 Feb

1.4K12 Sep

1.9K14 Sep

1.5K15 Sep

1.7K17 Sep

2.6K18 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.78%25 Sep

0.30%2 Oct

0.33%11 Feb

0.43%12 Sep

0.37%14 Sep

1.01%15 Sep

1.34%17 Sep

1.95%18 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes57.4%374 in total

Reposts8.0%52 in total

Replies1.2%8 in total

Quotes0.9%6 in total

Bookmarks32.5%212 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.