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    <lastmod>2025-03-03</lastmod>
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      <image:title>Andoni Mendoza</image:title>
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      <image:title>Andoni Mendoza - Austins Sweet and Sour</image:title>
      <image:caption>Austins Sweet and Sour is a personal project who's purpose is to identify the happiest and saddest spots in Austin. I overlaid tweets from the Austin area on a map of Austin and color-coded the tweets so that happy tweets show up as red, sad tweets show up as blue, and neutral tweets as green. By looking at which areas of the map have clusters of red markers, you can identify where Austin has the happiest tweets. I streamed tweets using Twitter’s API and sent them through a sentiment classifier API which returned whether the tweets had a positive, neutral, or negative tone. I stored the tweets on a database and wrote a small API to return them. There is also a statistics page where I discuss which day of the week and which hour of the day had the happiest and saddest tweets.</image:caption>
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      <image:title>Andoni Mendoza</image:title>
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    <loc>https://www.andonimendoza.com/andoni-mendoza-1</loc>
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    <lastmod>2026-02-16</lastmod>
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      <image:title>Andoni Mendoza (Copy) - Austins Sweet and Sour</image:title>
      <image:caption>Austins Sweet and Sour is a personal project who's purpose is to identify the happiest and saddest spots in Austin. I overlaid tweets from the Austin area on a map of Austin and color-coded the tweets so that happy tweets show up as red, sad tweets show up as blue, and neutral tweets as green. By looking at which areas of the map have clusters of red markers, you can identify where Austin has the happiest tweets. I streamed tweets using Twitter’s API and sent them through a sentiment classifier API which returned whether the tweets had a positive, neutral, or negative tone. I stored the tweets on a database and wrote a small API to return them. There is also a statistics page where I discuss which day of the week and which hour of the day had the happiest and saddest tweets.</image:caption>
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      <image:title>Andoni Mendoza (Copy)</image:title>
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    <loc>https://www.andonimendoza.com/andoni-mendoza-2</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2026-02-16</lastmod>
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      <image:title>Home (Copy) (Grey White) - Austins Sweet and Sour</image:title>
      <image:caption>Austins Sweet and Sour is a personal project who's purpose is to identify the happiest and saddest spots in Austin. I overlaid tweets from the Austin area on a map of Austin and color-coded the tweets so that happy tweets show up as red, sad tweets show up as blue, and neutral tweets as green. By looking at which areas of the map have clusters of red markers, you can identify where Austin has the happiest tweets. I streamed tweets using Twitter’s API and sent them through a sentiment classifier API which returned whether the tweets had a positive, neutral, or negative tone. I stored the tweets on a database and wrote a small API to return them. There is also a statistics page where I discuss which day of the week and which hour of the day had the happiest and saddest tweets.</image:caption>
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    <loc>https://www.andonimendoza.com/expiramenting</loc>
    <changefreq>daily</changefreq>
    <priority>0.75</priority>
    <lastmod>2026-02-16</lastmod>
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      <image:title>Expiramenting - Austins Sweet and Sour</image:title>
      <image:caption>Austins Sweet and Sour is a personal project who's purpose is to identify the happiest and saddest spots in Austin. I overlaid tweets from the Austin area on a map of Austin and color-coded the tweets so that happy tweets show up as red, sad tweets show up as blue, and neutral tweets as green. By looking at which areas of the map have clusters of red markers, you can identify where Austin has the happiest tweets. I streamed tweets using Twitter’s API and sent them through a sentiment classifier API which returned whether the tweets had a positive, neutral, or negative tone. I stored the tweets on a database and wrote a small API to return them. There is also a statistics page where I discuss which day of the week and which hour of the day had the happiest and saddest tweets.</image:caption>
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