Someone's Always Watching: Network Implications of The Gross National Happiness Index

Remember our discussion about networks? Well, Facebook has been tracking status updates for the past two years. (For those of you concerned about what they've been reading—what exactly have you been posting, hmmm?—they assure the public that all data collected was stripped of indentifying markers, so no one is actually tracking how many times you posted while you were supposed to be doing something productive, like, say working.) So what have they been tracking? Words. According to this article from the New York Times, they've been counting how many times you've said things like "Woo-hoo!" or "Yay!" or "doubt" or tragic" or "sad". They've taken this data and found patterns relating to the days of the week, holidays, celebrity deaths, and national events, resulting in the United States Gross National Happiness Index.

Essentially, the more positive words in your status, the more positive a day it is. Facebook researchers defined positive and negative using Linguistic Inquiry and Word Count software. The patterns they've found aren't necessarily anything that we probably haven't already intuited: Mondays are no one's favorite, on Friday's we're full of anticipation for the weekend, and everyone's relaxed on holidays. Markerters are probably salivating at the chance to peruse this data as it has effectively collected more information than most SEO strategies in the same time period, but it does make you think about the vast amount of data floating around on the web—and who's using it for what purpose.

I bring this back to our discussions on networks because I'm curious to what extent our Facebook statuses are influenced by our peers. For example, on Monday morning are you more likely to post a "Blah, it's Monday" type message because you want to commiserate with your peers? Similarly, on holidays are your messages more upbeat in an effort to share the holiday with others? Wired has already shown us how we can study the spread of happiness through a network, and we have seen from other data the influence our networks exert—can we extend this to emotional states as well?