Community Data Science Workshops (Spring 2016)/Day 2 Projects/Twitter

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In this project, we will explore a few ways to gather data using the Twitter API. Once we've done that, we will extend the example code to create our own dataset of tweets. In the final workshop (Nov. 5), we will ask and answer questions with the data we've collected.

Goals[edit]

  • Get set up to build datasets with the Twitter API
  • Have fun collecting different types of tweets using a variety of ways to search
  • Practice reading and extending other people's code
  • Create a few collections of Tweets to use in your projects

Prerequisite[edit]

To participate in the Twitter afternoon session, you must have registered with Twitter as a developer before the session by following the Twitter authentication setup instructions. If you did not do this, or if you tried but did not succeed, please attend one of the other two sessions instead.

Download and test the Twitter project[edit]

If you are confused by these steps, go back and refresh your memory with the Day 0 setup instructions

(Estimated time: 10 minutes)

Download the Twitter API project[edit]

  • Right click the following file, click "Save Target as..." or "Save link as...", and save it to your Desktop directory: https://mako.cc/teaching/2015/cdsw-autumn/twitter-api-cdsw.zip
  • The ".zip" extension on the above file indicates that it is a compressed Zip archive. We need to "extract" its contents. To do this on Windows, click on "Start", then "Computer". If you are a Mac, open Finder and navigate to your Desktop directory. Find twitter-api-cdsw.zip on your Desktop and double-click on it to "unzip" it. That will create a folder called twitter-api-cdsw containing several files.

Enter your API information[edit]

On Windows

On Mac

  • Start your text editor (probably TextWrangler if you installed it following our instructions). Navigate to the directory that contains the Twitter API project (probably something of the form ~/Desktop/twitter-api-cdsw).
  • Open up the file twitter_authentication.py in your text editor.
  • You will see four lines that include four variables in ALL CAPITALS that are being assigned, in the normal ways we learned about last session, to strings. At the moment, all of the strings say CHANGE_ME.
  • Go find the four keys, tokens, and secrets you created and wrote-down when you followed the Twitter authentication setup. Change every string that says CHANGE_ME into a string that includes the key, token, or secret you downloaded. Remember that since these are strings, we need to include quotations marks around them. Also make sure that you match up the right keys and tokens with the right variables.

Once you have done this, your example programs are set up to use the Twitter API!

Test the Twitter API code[edit]

On Windows

Start up PowerShell and navigate to the Desktop\twitter-api-cdsw directory where the Twitter API code lives. For example, if the Twitter API project is at C:\Users\YOURUSERNAME\Desktop\twitter-api-cdsw,

cd C:\Users\YOURUSERNAME\Desktop\twitter-api-cdsw

On Mac

Start a command prompt and navigate to the Desktop/twitter-api-cdsw directory where the Twitter API code lives. For example, if the Twitter API project is at ~/Desktop/twitter-api-cdsw,

cd ~/Desktop/twitter-api-cdsw

This will change you into the right directory.

ls will show you the source code files in that directory. One of the files is "twitter1.py", which has a ".py" extension indicating that it is a Python script. Type:

python twitter1.py

at the command prompt to execute the twitter1.py Python script. Wait a little while while your computer connects to Twitter. You should see a series of tweets run by your screen. If you don't, let a mentor know.

Potential exercises[edit]

Who are my followers?

  1. Alter code example 2 (twitter2.py) to get your followers.
  2. For each of your followers, get *their* followers (investigate time.sleep to throttle your computation)
  3. Identify the follower you have that also follows the most of your followers.
  4. How many handles follow you but none of your followers?
  5. Repeat this for people you follow, rather than that follow you.

Topics and Trends

  1. Alter code example 3 (twitter3.py) to produce a list of 1000 tweets about a topic.
  2. Look at those tweets. How does twitter interpret a two word query like "data science"
  3. Eliminate retweets [hint: look at the tweet object! https://dev.twitter.com/overview/api/tweets]
  4. For each tweet original tweet, list the number of times you see it retweeted.
  5. Get a list of the URLs that are associated with your topic.

Geolocation from Search API

  1. Get the last 50 tweets from Ballard.
  2. Get the last 50 tweets from Times Square.
  3. Using timestamps, can you estimate whether people tweet more often in Ballard or Times Square?
  4. A baseball game happened today (May 11) between the Seattle Mariners and the Tampa Bay Rays. Using two geo searches, see if you can tell which city hosted the game. Note: if you do this some other day, you should pick a new sporting event.

Geolocation

  1. Alter the streaming algorithm to include a "locations" filter. You need to use the order sw_lng, sw_lat, ne_lng, ne_lat for the four coordinates. (Recall Control C will stop an active process like the stream.)
  2. What are people tweeting about in Times Square today? (Bonus points: set up a bounding box around TS and around NYC as a whole.)
  3. Can you find words that are more likely to appear in TS?
  4. Boston is playing Houston in baseball right now. Set up a bounding box around the Houston and Boston. Can you identify tweets about baseball? Who tweets more about the game? Can you tell which team is the home team? (you can use d = api.search(geocode='-95.355549,29.757480,5mi) to get Tweets from Houston. Use Google or Bing maps to get a similar bounding box around Fenway Park).

Congratulations!!!![edit]

You now know how to capture data from Twitter that you can use in your research!!! Next workshop we'll play with some fun analytical tools. In the meantime, here are a few words of caution about using Twitter data for science.