Spy Gains from Time Magazine

The following are quotes from page 16 if you want to see the graph in all of it's parts there from the July9th/July15 Time Magazine double issue.

What Social Big Data can do:

Predicting trends through tweeting:
By studying sharing patterns, sceintists at MIT can predict the total number of retweets a tweet will receive over time, based on who and how many people retweet it within the first 5 minutes.
Payoff:
Athough the algorithm's average margin of error is 40%, it could help companies perfect their social-media messaging and allow brands to rapidly quantify celebrities' influence for twitter marketing campaigns.

Rewrite History?
Well. Kind of. By creating a social graph for 18th century Boston based upon historical Group membership rosters, a Duke professor found the most connected revolutionary: Paul Revere.
Payoff:
There's not much serious potential impact, but it's fun to think about: if King George had had access to mobile phone metadata in 1773, he might have been able to thwart the Boston Teapartyers.

Create Success?
By outfitting workers with audio-visual sensors, an MIT professor found a literal formula for success: the highest performing subjects used short statements and had diverse social networks, for example.
Payoff:
Consultants employ similar tactics to help companies improve overall performance, but the hyper-targeted sensors--albeit a bit creepy sounding--could also benefit individual employees

Manage disasters?

By analyzing whom Ivory Coast residents talk to on a regular basis(using geo-tagged phone data), researchers at the University of Birmingham found that quarantines would not slow the spread of most diseases.

Payoff:
Could help authorities reallocate resources toward disease awareness campaigns:if just 1% of the population were told to educate their friends, the researchers found, the message would spread effectively.

end quote from page 16 of the July9th/ july 15th 2013 Time magazine double issue.

except for the question marks on the headings this all was a complete quote from page 16 in regard to the graph bubbles there.

So, some information will help mankind that is gathered by institutions of learning and companies and governments and some information is going to harm mankind. Like all new technological tools people are usually both harmed and helped by all new devices depending upon the motivations of those who use those devices and instruments.