Queriable Quandaries in Constructing Digital Dictionaries

Short article today.

I was reading an interesting article this morning in the New York Times that discussed the limitations of traditional dictionaries when it comes to staying up-to-date on the latest slang. You can read it here:

http://www.nytimes.com/2015/10/04/technology/scouring-the-web-to-make-new-words-lookupable.html

Now, the purpose of apps like Wordnik is to identify words use on the Internet as “lookupable.” That is, these apps define a given word’s relevancy in everyday speech and log it as something that could be used by others on a broader scale. While Ms. McKean’s effort to unearth English’s “missing words” is certainly valiant, I’m going to be blunt and say that I feel it’s a bit of a futile quest due to the pace of our rapidly mutating languages. Moreover, the volatile nature of online languages makes me question whether Ms. McKean and Wordnik are really focusing on ‘the right thing.’ There’s little point in hunting down vagabond words and tossing them into the dictionary if their progenitors are sure to rise moments later as an endgame pursuit. But what we can focus on, using the data we gather on “lookupable” words, is the structure that emerging terms share.

Let’s use Ms McKean’s example of “roomnesia.” The article defines this word as “a condition in which people forget why they walked into a room,” its power deriving from the fact that it is a clever portmanteau of ‘room’ and ‘amnesia.’ Perhaps I am being too closed-minded at the moment, but most of the words that qualify for possible inclusion in Wordnik are portmeanteaus. In fact, the article lists a slurry of clumsy portmanteaus before examining roomnesia. In this case, it seems more appropriate to document the mechanical structure of these hybrids rather than the meaning of the word itself. Following the logic of roomnesia, anything can be a -nesia. It seems we would gain a greater understanding of this word and its brethren if we could look up roomnesia on Wordnik and learn that tacking a -nesia onto the end of an existing word (a state of being or, in this case,a  simple noun) creates a portmanteau that implies forgetfulness in a certain situation.

Such an approach would free us from the confines of strict definitions when it comes to trendy terms that populate social media circles, because it implies that language on the Internet is highly mutable. But there is, of course, an issue of artistic flair when it comes to creating these new words. We all know the feeling of wondering where our sunglasses are when they’re actually on top of our head, but saying “sunglassesnesia” or “shadesnesia” just doesn’t roll off the tongue like roomnesia does. How, then, would we create a new word that encapsulates this feeling of sunglasses dysphoria? Maybe Wordnik can help us out, if it devotes its energies to dissecting the mechanical bases and creation of the -nesia family.

Again, my thoughts aren’t meant to downplay Ms. McKean’s work (or Wordnik’s, if we want to give credit to our machine companions). But can Big Data alone, touted by businessmen and laymen alike as the divining rod that will draw up useful assets from the digital morass like potable water, grant us full insight into what people do and why they do it? It can pinpoint trends and trend words, but it’s up to linguists themselves to make the judgment calls. They can identify what the roomnesias and dronevertisings of the future embody – and they can predict how they will morph to suit new social contexts and influence the creation of new words through their mechanical components. We have to help our mechanical friends, after all, just as much as they help us. And through this union, we can at least begin to grasp at the multiplicity of being human.

I’m sure most of Big Data’s proponents realize this, by the way. It’s just easy to lose sight of how we collaborate with our machines as they become more human-like.

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