Quantity and Quality
A case of accidental prioritization.
In January, I started using Beeminder to track my blogging. For each post, I’ve been adding a data point with a value of one, with a goal pace of about four posts per week. However, because each post had the same value, I had inadvertently set my sights for quantity over quality. If it doesn’t matter how well I write, quality suffers at the expense of quantity1.
In order to get around this, I should change what is being measured. Naively, I could change my goal to be N words per week (where N is initially my historic rate), but this would result in a different accidental prioritization of quantity over quality: I would write longer posts, not necessarily better posts.
Instead, I’m developing a quality measurement using natural language processing, and incorporating it into
mindfeed. I’m unsure how exactly to calculate quality, so instead of guessing, I’m developing a set of features each of which I’ll mind2 with Beeminder separately. I’ll then manually rate my previous posts and develop a model which can assign a rating to a post using the features. Eventually, I may ask some prototypical readers to rate my posts. I could then develop a model for each set of ratings.
One feature will be length, thought as mentioned above, it cannot be used on its own. I’ll also look at vocabulary diversity using the count of types as well as an information-theoretic approach. I will also be tracking readability measures such as the Flesch–Kincaid index. Another aspect to consider is uniqueness relative to previous posts. This can be simple, such as how many new words were introduced in this blog post, or more complex, such as vector-space distance.
Measurements are important, as they do change behavior, but what we measure can sometimes have unintended consequences. Choose your metrics carefully.
Once I realized I was doing this, both quantity and quality plummeted.↩
mind, verb: to track data with Beeminder.↩