Accidental Reading
a project to monitor all articles I read digitally over a year to better understand patterns of personal information consumption
So you feel productive. You open your laptop and start on your project. But then an email arrives containing articles with irrelevant, but enticing names starting with “40 tips that will change…”, “The most important… “, “The biggest reason, why…” - we, you get the gist. You decide to “quickly check-it out”. You click on the link and skim the article. It contains another reference. You click on it too. Skim another source. Another link. Thirty minutes later, you, mentally distracted and exhausted, trying to get back to work. In the aftermath, you realize that you just acquired some questionably useful information but have not progressed on the task at hand.
I suspect the above scenario is not uniquely my problem, and many many more fell prey to catchy headlines of random online content. I call it “accidental reading”. It is not the reading one plans, but the one that sneaks on your plate the way parents sneaked broccoli onto your plate as a child. Except, the nutritional value of this kind of information is questionable. Some might justify it as serendipitous virtual discovery, some may argue that this type of reading can uncover the surprising number of confluences . But I refuse to believe that clicking another Medium article “10 Javascript Hacks every developer should know” will improve my coding (or a more low-brow version “10 Lifehacks that every developer should know” will improve my productivity). In fact, I suspect that it robs me of time and mental concentration that I could invest in things I care about.
Instead of speculating on the value of my information diet, I have decided to approach the issue scientifically and just measure it. During 2020 I recorded all the articles I read. My system was extremely simple: I kept a markdown file and every time I read an article, I dropped a link to the bottom of the list. At the same time, if I wanted to read an article but did not want to go down the rabbit hole of bottomless internet content, I placed an article URL on top of the file. So here we are, at the end of 2020. The file is complete and it’s time to draw empirical conclusions.
Final Project published as Observable Notebook
Stack:
- Article Data tracking: markdown
- Book Data tracking: with Goodreads
- Text scraping: Newspaper 3K
- Content Categorization: Google Content Classification
- App: written as Observable notebook