Editing Community Data Science Workshops (Fall 2015)/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 | In this project, we will explore a few ways to gather data using the Twitter API. Once we've done that done, we will extend this to code to create our own datasets of tweets that we might be able to use to ask and answer questions in the final session. | ||
== Goals == | == Goals == | ||
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* Right click the following file, click "Save Target as..." or "Save link as...", and save it to your Desktop directory: http://mako.cc/teaching/2015/cdsw-autumn/twitter-api-cdsw.zip | * Right click the following file, click "Save Target as..." or "Save link as...", and save it to your Desktop directory: http://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 | * The ".zip" extension on the above file indicates that it is a compressed Zip archive. We need to "extract" its contents. To do this, click on "Start", then "Computer" on Windows or open Finder and navigate to your Desktop directory if you are a Mac. Find <code>twitter-api-cdsw.zip</code> on your Desktop and double-click on it to "unzip" it. That will create a folder called <code>twitter-api-cdsw</code> containing several files. | ||
===Enter your API information=== | ===Enter your API information=== | ||
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python twitter1.py | python twitter1.py | ||
at the command prompt to execute the <code>twitter1.py</code> 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 | at the command prompt to execute the <code>twitter1.py</code> 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 staff member know. | ||
== Potential exercises == | == Potential exercises == | ||
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'''Who are my followers?''' | '''Who are my followers?''' | ||
# | # Use sample 2 to get your followers. | ||
# For each of your followers, get *their* followers (investigate time.sleep to throttle your computation) | # For each of your followers, get *their* followers (investigate time.sleep to throttle your computation) | ||
# Identify the follower you have that also follows the most of your followers. | # Identify the follower you have that also follows the most of your followers. | ||
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'''Topics and Trends''' | '''Topics and Trends''' | ||
# | # Use sample 3 to produce a list of 1000 tweets about a topic. | ||
# Look at those tweets. How does twitter interpret a two word query like "data science" | # Look at those tweets. How does twitter interpret a two word query like "data science" | ||
# Eliminate retweets [hint: look at the tweet object! | # Eliminate retweets [hint: look at the tweet object!] | ||
# For each tweet original tweet, list the number of times you see it retweeted. | # For each tweet original tweet, list the number of times you see it retweeted. | ||
# Get a list of the URLs that are associated with your topic. | # Get a list of the URLs that are associated with your topic. | ||
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'''Geolocation''' | '''Geolocation''' | ||
# 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. | # 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. | ||
# What are people tweeting about in Times Square today? (Bonus points: set up a bounding box around TS and around NYC as a whole.) | # What are people tweeting about in Times Square today? (Bonus points: set up a bounding box around TS and around NYC as a whole.) | ||
# Can you find words that are more likely to appear in TS? | # Can you find words that are more likely to appear in TS? |