Wolfram Alpha nerd-crunches your Facebook activity, turns your social life into data

All those likes and posts pics turned into raw data.

By Evan Dashevsky, TechHive |  Unified Communications, Facebook, Social Networking

Every time you like a picture of the meal your friend posted to Instagram or tweet about loving that horribly irresistible "Thrift Shop" song despite yourself, you have created a data point. Congratulations! Crunching all that publically available data is of obvious interest to the security and marketing folks (and therefore also privacy advocates), but it is also becoming an increasingly important tool for social research.

Wolfram Alpha, the data-driven Google for math nerds, has created a free service that will analyze your Facebook activity and reinterpret it as visual graphs and interactable data points. For example, the service was able to devise that my average FB post length is 14.66 words, my top utilized significant word (excluding it, and, etc.) was "know," and my most-liked post was a picture of a slice of pie I had last Thanksgiving. Wolfram will also break down your most active time for FB activity (Thursday at 3:30 PM is a big time for me) and graph the socio-demographics of your friends including age, marital status, and even social-connectedness.

That's all just a taste of what Wolfram's Personal Analytics report can show, and for the individual, it's all a bit of interesting social media naval gazing. But beyond sating our inner narcissist, the Wolfram team has used their technology to gather anonymized Facebook data points from more than a million users, run it all through the mathematical wringer, and cull the results into a giant data ball of social activity. The in-depth blog post describing Wolfram's findings is interesting and well worth the read, but we've highlights some of the standout findings below.

Data points with legs

Wolfram's findings show how people on Facebook use the site to connect during different parts of their life (though, as FB is a mere nine years old, this very well may change in time). For example, through the age of 40, the median age of our friends tends to be close to our own. Once users gets into their 50s, the distribution of ages begins to level out to include many younger users as well. These younger parts of one's social circle are presumably the result of a thinner field of older users diluted by younger connections from one's work and community.

The visualization to the right shows how the makeup of your social circle's marital statuses change over time. As you might expect, those self-reporting as "married" explodes as people move towards their thirties, taking over from those who are "single" or "in a relationship" ("engaged" also has a moment in people's 20s and then falls over time). As one's friends reach age 50, a sliver of "widowed" creeps in to the makeup and slowly expands thereafter.

The data also separates posts as separated by interests. The most popular word in posts catgorized as being about technology is "phone," and the most-used word in posts about food and drink was "beer" (which, for the record, just barely edged out "food").

The choice of post topics as broken down by male and female freinds falls well within gender stereotypes with men being far more likely to post about sports and technology, and women more likely to post about personal moods or family and friends.

We are all in the Matrix, get used to it

Over the past decade, the public has come to understand how a general mood and opinion can be culled from social media activity as exemplified by the top Twitter trends and YouTube viewing data. As we enter further into the mobile age and begin to carry the Internet around on our face, large meta-analysis of human activity will be easier than ever. The Zeitgeist will be chronicled in real-time and will only be a few clicks away.

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Originally published on TechHive |  Click here to read the original story.
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