I am enrolled in a course being offered by Worldview in Stanford called “Behind and Beyond Big Data“. As a part of this I am learning a lot about how the big data is being used in various interesting ways. In addition, a couple of other things that I saw on TV or heard in the social media also has captured my interest.
Tweets predicting rates of heart attacks. https://goo.gl/2iInWM%5B/caption%5D
Predictive Modeling based on Facebook Likes
Michal Kosinskia, David Stillwella, and Thore Graepelb from the University of Cambridge and Microsoft designed an experiment to see if the Facebook Likes of a person is a predictor of “private traits and attributes” of a person such as age, intelligence and sexual orientation. They describe their research here. A very large sample of facebook users contributed voluntarily to the research by participating in myPersonality initiative. They also manually inspected the volunteers’ facebook profiles in some cases to infer additional information such as the ethnic origin. It is a fascinating experiment. If you are interested in checking how well the system predicts your traits and attributes, try it out at Apply Magic Sauce.
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Last week we heard about Apple vs FBI in the fight over a locked iPhone containing presumably valuable data regarding the San Bernardino attackers who killed 14 innocent people. Last night we heard about a gunman who randomly shot people in Kalamazoo, MI who happens to be a driver for Uber. There is no direct connection between the topic of this blog and these two incidences though some indirect link exists and I will leave it to your imagination.
Regardless of our individual positions on Apple’s stand, I would be curious to know what they find in the iPhone that they cannot find elsewhere. In this so well connected and cloud driven world where every vendor seem to want you to sync all of your information with their cloud services, you must be pretty deliberate and careful about not syncing your data with other cloud based systems. A bigger question I have is, with such vast amounts of available data and sophisticated analysis tools, what prevented law enforcement from picking up something like this? Impure data? Inconclusive evidence?
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Many of us are saddened by the Boston Marathon bombings and are relieved that the ordeal has come to an end. Or, has it? I think each of us will take our own time to reflect on the events, digest both the reliable as well as the mis-information that is being directed us from all directions, and derive our own conclusions. As I wrote in my last post, various technologies played important roles in identifying the suspects and eventually capturing one of them. They brought to light several important things – explosion of technologies, how the law enforcement relied on distributed technologies (video tapings from sources other than Law enforcement), social media and crowd-searching (crowd sourced searching), and thermal imaging.
Frankly what got lost in all of these discussions is how every one of these items is far more complicated than the positive aspects which helped us in the end. And most importantly, what led to the surviving suspect was an actual curious human being and not the technology. Quite obviously, every step of the way, there were pitfalls – privacy, security, misuse of captured information, dangers of subjectivity arising from crowdsourcing the search whi has a high probability of the wrong people being implicated etc. etc. And the massive data that was helpful in cases like this and others is the “Big Data“.
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