Big Booth Words Is Watching You!
Dear English-B Interpreter Friends,
(First, my letter to you to using words from Post #10)
Late last year, I interpreted at an event on geographic information systems. The developers and speakers were so enthusiastic about ascertaining and exploring ways to utilize the terabytes upon terabytes of information we can now gather that they all but sang cult-like paeans to big data from the stage. At the event, everything sounded marvelous: using massive data sets to combat crime, improve education, plan agricultural strategies for the 21st century, etc. Of course, recent scandals show us how a more tendentious use of this trove of information may cause slight friction, to say the least (Assange, Snowden, Greenwald, etc.).
Which brings me to what dirty secrets I drudged up about every one of my readers this week (cue evil laugh). Until recently, you were all reading these digests in blissful anonymity, but the new online program to which I switched to overcome the managerial quandary caused by trying to misuse Apple mail as a digest manager offered me some unexpected Easter eggs. On a Big-Brotheresque leveI, I was surprised to find my new program individually lists who actually opened my e-mail (I can tell who actually seems to care), where (not e-mail specific) the digest is read (I can envy you readers who perused this digest in Alaska and India), and which specific links you individually click on (I can see your true preferences or even disinterest). Therefore, in case any of you care what I think, please feel free to deceitfully click on all the links henceforth and make me feel like my time is worth it.
But, like all data sets, as the ardent advocates at the referenced event showed rather successfully, mass information can (and should) be put to beneficial use. Joking aside, I choose to focus on the positive, and what the statistics truly emphasized was:
- that more of you opened the e-mail than industry average (therefore I have decided to continue sending out this digest);
- that practically none of you clicked on the video links (therefore I am not going to send video links this week and see if any of you object by sending me a personal e-mail);
- that only a precious few of you clicked on all links, and that many more clicked an average of 3-4 links (therefore I know how and to what extent my steadfastreaders use this digest for studying; I know others use it merely for quick, clever entertainment; and I can also gauge which words are likely brand new); and
- that the most clicked links were about Brazilian corruption and US involvement in the Ukraine imbroglio, and not the article about Jews, money and Chinese perceptions, which I personally thought was the freshest perspective on the last list (therefore a new experiment of sending out only links based on a specific theme should help me find the pattern here; do my readers click for content or for the specific word being highlighting?).
I have more interesting things to do than set up an online dragnet to systematically figure out who reads what and when, but occasionally studying the overarching database will give me the feedback I need to tweak these digests to maximum effectiveness.
Data is great. It all depends on how it’s used.
*** FIVE WORDS (IN BIG-DATA CONTEXT) TO BRING INTO THE BOOTH ***
* As used in the body of this very thorough Ars Technica article breaking down the idiotic term of, but gorgeous concept behind, big data.
* As used in the body of this CNN post on the status of Julian Assange in the Ecuadorian embassy in London to avoid extradition to Sweden.
* As used in this body of The Economist’s review of Acadamy-winning The Imitation Game, which beautifully portrays Alan Turing’s code-breaking work during WII and development of the early computer.
* As used in the body of The Guardian’s article on Greenwald, Snowden, Dotcom and Assange’s virtual debate last year.
* As used in the title of this short NYT piece on the security vulnerability of the healthcare industry.