WHY IT MATTERS: Digital Transformation

In real life, in the natural course of conversation, it is not uncommon to talk about a person you may know. You meet someone and say, “I’m from Sarasota,” and they say, “Oh, I have a grandparent in Sarasota,” and they tell you where they live and their name, and you may or may not recognize them.

An email from Aleksandr Kogan sheds light on exactly how much your Facebook data reveals about you, and what data scientists can actually do with that information. The researcher whose work is at the center of the Facebook-Cambridge Analytica data analysis and political advertising uproar has revealed that his method worked much like the one Netflix uses to recommend movies.

With the explosive growth of online activity and social media around the world, the massive amount of real-time data created directly by populations of interest has become an increasingly attractive and fruitful source for analysis. Despite the limitation that social media users in the United States are not a random sample of the US population [7], there is a wealth of information in these data sets and uneven sampling can often be accommodated.

Indeed, online activity is now considered by many to be a promising data source for detecting health conditions [8, 9] and gathering public health information [10, 11], and within the last decade, researchers have constructed a range of public-health instruments with varying degrees of success.

Fine-tuning these algorithms is key to improving large-scale analysis of social media, whether the goal is to measure the caloric content of a tweet or to find the next developing news story. These technologies represent new ways of finding and understanding the conversations we're having as a country -- chatter that is increasingly moving online.

“During the 100 days before the relationship starts, we observe a slow but steady increase in the number of timeline posts shared between the future couple.”

Only Facebook could create Safety Check, not because of resources as you might expect, but because Facebooks lets employees build crazy things like Safety Check and because only Facebook has 1.5 billion geographically distributed users, with a degree of separation between them of only 4.74 edges, and only Facebook has users who are fanatical about reading their news feeds. A small team couldn’t build a big pipeline and index, so they wrote some hacky PHP and effectively got the job done at scale.

This paper details how Facebook build Safety Check