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  Whether the Space stays on top of your list.
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  # HISTORY OF THIS PROJECT
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- 1. Tweet replies were extracted using Twitter's API, then saved to a CSV file.
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- 2. Due to Twitter's dev policies, I cannot share that file, so I ran sentiment analysis on those tweet replies outside of this app and saved the results to the `df_redacted.csv` file.
 
 
 
 
 
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  Whether the Space stays on top of your list.
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  # HISTORY OF THIS PROJECT
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+ 1. This project began when I saw the Twitter announcement by Facebook that they were re-branding to Meta, and I was curious what the public sentiment of this announcement would be. I suspected that it would be more negative than positive due to various reasons, but I wanted to find out nonetheless.
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+ 2. Tweet replies from the Facebook/Meta announcement were extracted using Twitter's API, then saved to a CSV file.
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+ 3. Due to Twitter's developer policies, I cannot share that file of extracted Tweet replies and associated metadata, so I ran sentiment analysis on those Tweet replies outside of this app and saved the results to the `df_redacted.csv` file. This file DOES contain the ids of the tweets which were analyzed, which is allowed per Twitter's policies. The sentiment model I used was VADER.
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+ 4. In future revisions, I plan on finding a way to post my code from the extraction portion of the project, along with demonstrating various methods of cleaning the Tweets and how that affects the outcome of the analysis.