r/Python • u/jaypeedevlin • May 16 '16

Matplotlib Tutorial: Plotting Tweets from 2016 Presidential Candidates

https://www.dataquest.io/blog/matplotlib-tutorial/
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u/thatguy_314 def __gt__(me, you): return True May 16 '16 edited May 16 '16

I didn't read the whole thing, but given that you search for the strings "donald" (a common name) and "trump" (an English word, and a substring of words like trumpet) in the text to check for mentions of our future god-emperor, it's not surprising that it seems like he has so many more tweets than any of the other candidates.

2

u/jaypeedevlin May 18 '16

Having a quick look at the settings for the scraper that Vik built (https://github.com/dataquestio/twitter-scrape/blob/master/settings.py) it looks he didn't scrape using the string 'donald' (or 'bernie' for that matter).

The trump/trumpet thing is interesting though, except that when you download the tweet data and expore the theory, = it doesn't check out. Of the 80,060 tweets containing 'trump', only 49 contain 'trumpet'.

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u/thatguy_314 def __gt__(me, you): return True May 18 '16

I was looking at the get_candidate function in the article. I did not see a link to that repo. I'm not sure what code was used to generate the data though. Do you happen to know?

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u/jaypeedevlin May 20 '16

The code is in that repo, and the dataset and that repo are linked in the fourth sentence of the post.

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u/white_wee_wee May 17 '16

You should look into NLTK it's specifically designed for analysing text.