What automatic tracker did you use? I would like to find out how I`m spending my own time online as well
I use arbtt, in combination with arbtt-graph to visualize data. (You don't need arbtt-graph to get statistics, it just makes them look pretty). arbtt might require some technical skills, like using a command line interface instead of a "point and click" interface.
I haven't used any, but if you're just interested in tracking Internet use, there are several browser plug-ins. These are probably the quickest and easiest to use. You almost certainly want something that runs entirely in the background (so avoid software that asks you to manually clock in and out; this is aimed at people who are tracking billable hours), and something that detects inactivity.
Btw, manual data collection is always worth considering. In this case, you wouldn't want to do it long term, and it might change your behavior, but it could still be valuable. In fact, manually tracking can provide a quicker feedback loop to learn things like "so that's what XXX minutes doing YYY actually feels like". And you don't get stuck fighting to install software or wondering if it's really working correctly.
I recently used an automatic tracker to learn how I was spending my time online. I learned that my perceptions were systemically biased: I spend less time than I thought on purely non-productive sites, and far more time on sites that are quasi-productive.
For example, I felt that I was spending too much time reading the news, but I learned that I spend hardly time doing so. I didn't feel that I was spending much time reading Hacker News, but I was spending a huge amount of time there!
Is this a specific case of a more general error?
A general framing: "Paying too much attention to the grouping whose items have the most extreme quality, when the value of focusing on this grouping is eclipsed by the value of focusing on a larger grouping of less extreme items".
So in this case, once I had formed the desire to be more productive, I overestimated how much potential productive time I could gain by focusing on those sites that I felt were maximally non-productive, and underestimated the potential of focusing on marginally more productive sites.
In pseudo-technical terms: We think about items in groups. But then we think of the total value of a group as being closer to average_value than to average_value * size_of_group.
This falls under the category of Extension Neglect, which includes errors caused by ignoring the size of a set. Other patterns in this category are:
For the error given above, some specific examples might be: