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      <image:title>Home - IMPACT OF IMMIGRANT VOTERS</image:title>
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      <image:title>Home - TWITTER IMMIGRATION SENTIMENT DETECTION</image:title>
      <image:caption>I originally pulled approximately 1 million tweets between the early election cycle in 2016 into about halfway through Trump's presidency in 2018. The goal was to be able to determine how public sentiment has changed on immigration over time and whether or not it is related to large scale events like elections or mass deportations. It became abundantly clear that trying to determine sentiment on a political subject is a difficult task, especially when you are trying to parse whether someone is "for" or "against" a particular political stance. So, I had to create a custom sentiment model by training on about 30,000 tweets we hand labeled at New American Economy.</image:caption>
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      <image:title>Home - UPSAMPLING VOTER PREFERENCE DATA</image:title>
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