Students for Urban Data Systems

at Carnegie Mellon University

Emojis of Pittsburgh

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by Dan Tasse and Jennifer Chou

What do people in Squirrel Hill talk about?

Or, more interestingly, what do people in Squirrel Hill talk about that people in other neighborhoods don’t? What is it that makes Squirrel Hill Squirrel Hill? That’s the question we set out to answer with this project.

words

Most frequently tweeted words in each Pittsburgh neighborhood

How it works

We gathered all tweets geotagged in Pittsburgh over about a year, from December 2013 to January 2015. We sorted them by neighborhood (using boundaries provided by the WPRDC) and used a modified TF-IDF algorithm to figure out what words were specific to each neighborhood. This algorithm counts the frequency of a word in a given neighborhood, and then adjusts the word’s final score based on how many other neighborhoods also use that word.

For example, “Steelers” is used a lot in Squirrel Hill, but it’s also used in many other neighborhoods, so it has a pretty low score. “Tunnel”, however, is quite popular in Squirrel Hill (mostly due to people grousing about tunnel traffic), but not elsewhere. Similarly, “10a” is a popular bus used to get around Pitt, but isn’t used elsewhere, so “10a” shows up a lot in Oakland.

10a

Tweets referencing the “10a” bus

An emoji is worth…

These words just represent what people are talking about on Twitter. What are people feeling? To answer that question, we looked to the emojis people are tweeting. Emojis are an interesting new form of communication: one character can often say more than a word, so they can tell us about where people like to do certain things, or maybe even how people feel.

emojis

Top emojis in each ‘hood

For example, we can see that the zoo is up in Highland Park, and that people like watching baseball and football and drinking beer on the North Shore. Obvious enough. But did you know how popular the swimming pool in Oakland is, or the Christmas tree lighting downtown?

Future work, and so what?

There’s still work to do, of course. One major challenge is algorithmic: How do we combine these posts from multiple people into a representative aggregate? A lot of these words/emojis are boosted by one person tweeting them multiple times. We don’t want one person to dominate the neighborhood’s tweets, but we do want an avid basketball fan to count more than someone who just tweeted about basketball once.

We hope this is the first step towards useful neighborhood guides. Imagine if you were moving to Pittsburgh for the first time, and looking for the right area to live in. Knowing that Squirrel Hill South has a lot of basketball fans, or that the top words in Lawrenceville are trendy bars or music venues, could really help you get a feel for the city and its many unique neighborhoods.

Try it out! http://emojimap.herokuapp.com

(Be patient; it’s on a free server so it’ll be a little slow.) And send any feedback or ideas to dantasse@cmu.edu.

Dan Tasse is a PhD student in Human-Computer Interaction at CMU. He’s interested in how we can use social media posts to help people understand their cities and neighborhoods better.

Jennifer Chou is an undergraduate studying Computer Science at CMU.

Author: eric@ericdarsow.com

CMU Leadership team: external relations

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