The 80/20 Rule reading was about how 80% of the time and effort we spend on things is ‘largely irrelevant’, pretty much fruitless. Well, that wasn’t the main point of the reading, but it was the point that resonated with me the most. I can see how it’s a pretty valid rule as it can be applied in the real world (if we ignore particulars, otherwise there’d probably be quite a few flaws). I find that every time I try to do work, 80% of the time is spent procrastinating and 20% is spent actually doing the work. Before my VCE exams, I spent 80% of my time stressing and worrying about it, and 20% studying. When working in groups, we all encounter that experience when the majority of the work is done by the minority.
“when i die i want my group project members to lower me into my grave so they can let me down one last time”
— no (@tbhjuststop) June 20, 2014
I spent a good 5 minutes laughing at those posts. This is what I spend 80% of my time doing ahahaha…haha….hah……. I need to be more productive with my life.
Moving on, this 80/20 rule can also be observed in terms of networks. In last week’s tute, Elliot had pretty much summed up the reading for us which made the reading so much easier to get through. If the usual academic reading is like swimming through mud, this reading was like swimming through water. Woohoo. Anyway, Eliot had compared the train network to the online network with two graphs; a bell curve and a log curve.
On the net, 80% of links point to about 15% of webpages – the hubs/connectors. Under the power law system, or the scale-free distribution, the number of links and webpages grow exponentially and are limitless.
If we compare this to a ‘random distribution’ with train networks, we can see that most nodes have only two links with the outliers having 1 or 3. These types of networks have peaks and limits. ‘Nature normally hates the power law’.
Unlike train links, the online network is likely to continue garnering more and more links in a pyramid scheme manner. If we take facebook for example, if the probability of someone sharing a link that I’ve shared is 0.1 and I have 100 friends, then that’d be 10 shares. If the pr is the same for my friends, then that’s an additional 100 shares.
Below I’ve attempted to illustrate the two types of distribution
