Last time, we took an content graph view of this elderblog. Now let’s take a word-count view. There is something pleasantly honest about word counts. They strike a thoughtful balance between weighing writing in too-literal (compressed file sizes) and too-abstract (post count) ways. Ribbonfarm has averaged 11,491 words/month over its 11.5 year history.
The two spikes in 2007 and in 2017 are explained by me flushing out a pile of private drafts when I started, and the publishing of the longform course participant essays respectively. The steady accumulation is even clearer in the cumulative word-count graph:
I finally made a proper Contributors page, and after much thought, decided to order it by word count. In the graph below, the red bar is the long-tail-rollup “Contributor” handle under which we publish one-off contributions (it would rank #3 if counted as a single author).
And here are the actual word counts for our 10k club. If I could figure out how to do it easily, I’d make the Contributors page show live word counts.
- Venkatesh Rao: 1,155,543
- Sarah Perry: 154,958
- Kevin Simler: 32,895
- David Manheim: 27,940
- Taylor Pearson: 20,164
- Tiago Forte: 19,879
- Carlos Bueno: 16,499
- Ryan Tanaka 16,138
- Mike Travers: 13,181
- Haley Thurston 13,002
- Adam Elkus: 11,749
- Brian Skinner: 10,410
A word count is the simplest measure of meaningful relative information. Individual words are part of common knowledge. The average adult reader does not expect to have to look up words in dictionaries when reading generalist content, and expects a fairly narrow density range.
There’s a couple more statistical views I’d like to do but don’t know how: a semantic content map (perhaps using the tf-idf algorithm), and an external impact analysis (using inbound link statistics). If someone wants to take a shot at those, I’ll feature the highlights on this blogchain.
About Venkatesh Rao
