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I wanted to do my first project on sentiment analysis. My goal is trying to do sentiment analysis on tweets that mention 'Uber' and see if there is correlation with the stock price: 'UBER'.

Problem is it went public this year, so I would need tweets from this year, my question is:

Is there any way of avoiding paying for the api: https://developer.twitter.com/en/pricing ? How can I get let's say 10,000 tweets of this year mentioning uber?

Or maybe, given I don't have any experience shall I instead try doing it on an already created dataset? ie https://www.kaggle.com/davidwallach/financial-tweets ? (problem here is that this data set only has 28k tweets, and if I filter for the ones only naming stock 'xyz', I will likely get only a hundred tweets...)

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  • $\begingroup$ You can definitely get the tweets for UBER keyword from twitter , without paying any money. $\endgroup$ – cap Dec 11 '19 at 0:56
  • $\begingroup$ Are you looking for code which you can use directly to get the tweets related to Uber? Also I wouldn’t use financial tweets dataset for the given situation. You should definitely try getting the tweets and link it to your financial data separately.. $\endgroup$ – cap Dec 11 '19 at 0:58
  • $\begingroup$ I am a newbie. Yes I am looking for code to use it to get tweets that either mention uber or have the hashtag uber. (of course not the exact code, I know some python so, at least some template to start playing around). $\endgroup$ – Chicago1988 Dec 11 '19 at 11:34
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First you need to setup the twitter api and get the credentials and add those to the congig.cfg file linked here- https://filebin.net/5a6lfserhqzjg93a/config.cfg?t=dcqh998i

Afterwards you can use this link https://filebin.net/nfeju0bjvh8tocl3/tweetering.py?t=dy6bk7x5 to download the tweets which contain Uber. Just run it on command line using - python tweetering.py Uber

Hope it works for you. You can also find many links on medium.com where you can find the complete twitter sentiment analysis steps, reading which you will understand a lot of things.

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