Language Research, Social Network Analysis

How the Twitterverse is Contributing to Language Research

I recently joined Twitter. I am beyond fashionably late to this party, but Twitter has been on my linguistics radar for several years, thanks to the fact that many researchers have used tweets as data sets to study various aspects of language change and use.

Personally, I love the idea of hashtags as meta-commentary or as a type of paralinguistic cue (#SorryNotSorry comes to mind), but I’ve also listened to presentations where hashtags were used to track the spread of breaking news, as well as how it was possible to tell the trending hashtags that evolved organically versus the hashtags that were purposefully created (like those shown at the bottom of your TV screen during your favorite television series)—for the organically evolved, there are differences in wording or spelling, where as created hashtags tend to all spring up at the same time and in the same format.

But one of the big draws is the sheer amount of data that Twitter can provide. Searching a hashtag brings up thousands of tweets, and it’s here that language researchers are looking for insights. Since August I’ve come across two articles about a study that turned to Twitter to investigate Spanish dialects and discovered the existence of two “superdialects” whose usage doesn’t depend on geographic region. Rather, one dialect appears to be used more often in cities, and the other in rural areas. You can read the first article I found, from the MIT Technology Review here, and/or a more recent write-up of the same article I found on here.

Another way that researchers are using tweets as data are to reveal the overall mood of Twitter users on different days of the week and at different times throughout the day. This Buzzfeed article has some fun color-coded (if a little confusing) charts showing just that. The study uses specific search phrases like “feeling happy” or “hungover.” And with a huge data set culled from these search terms, their findings are probably reliable….to a point.

But as we all know, the words we use aren’t always meant literally. The lack of paralinguistic cues like facial expressions, body positioning, and tone of voice in online communication, combined with the 140 character limit, means that taking a phrase out of context isn’t going to reveal a foolproof data set of mood indicators. The sentiment analysis of tweets and Facebook posts are a big challenge to computational linguists—just think of how many meanings the word “like” can have online, or how much difficulty Sheldon Cooper from The Big Bang Theory has with recognizing sarcasm, and you have an idea of the possible pitfalls.

Does anyone else have examples of Twitter being used as a data source for research?

If you’re on Twitter—let me know! I’m always looking for cool people to follow. And if you want to return the favor, you can follow me at @l_g_johnson


As a bonus, yesterday was National Punctuation Day! Check out this fun Mental Floss article about lesser-known punctuation—I think it pairs well with the above section on paralinguistic cues. They’re like less colorful emojis!

Social Network Analysis

I Know a Guy: The Power of Triadic Closure

First, I read an article about why submitting a resume without an “in” is not typically successful.

Then, I read a blog post written by a former classmate about social networks.*

Finally, the movie The Social Network was on TV today.

What do all these signs point to? A blog post about trust and social networks!

I was lucky enough to take a class outside my department in my last semester. It was a class called Social Network Analysis, and it. was. amazing. Not only because it made me do math problems for the first time since the GRE, but because it gave me a vocabulary to discuss certain aspects of relationships between people and places. For example, the fancy phrase in the title, triadic closure? Really, that means that if you are friends with Alan, and friends with Betty, then it is likely that Alan and Betty will become friends as well, mostly because they already have something in common: you. This also works with institutions. How many people went to a college because your friends were planning to go there too? Or you brought a friend to your favorite yoga studio and they started regularly attending class, even when you didn’t go too? All examples of triadic closure.

Anyway, after reading that article about networking to find an “in,” I’ve been thinking about the importance of trust in social networks. If the importance of networking, of “knowing someone” in the right position, is the key to getting inside, whether it’s a job, a party, whatever, then what’s the trust threshold? Telling people about a party may not be a big risk to your social standing, and neither is sending along a job posting that you saw online. But what about when that job is at your company?

If your connection ends up applying and mentions your name, all of a sudden your judgement and reputation are tied to this application. You may get asked your opinion of this person, maybe even your opinion of their work ethic. Like anyone, I have good friends and acquaintances, but can I comfortably comment on the work ethic of all of them? Heck no. Probably only a handful. And that’s because I’ve worked with them on something. I could give many of the others a decent character reference, but that’s it. Not because I don’t want to help them, but because whatever I say will have weight and managers and HR people want to hedge their bets and find someone who will be a good fit as quickly and painlessly as possible.

So when I think of all of these formal networking events, I wonder how valuable they really are. For an introvert like me, who needs to build up energy and courage to attend these kinds of functions, I think my time would be better spent joining groups with like-minded people, and then using those triadic closures to create others. Because Social Network Analysis tells me that’s much more likely. And definitely more fun.


*For the quantitatively-minded among you, check out the blog of my friend and fellow MLC alum, Casey Tesfaye: Or just click on the hyperlink above!