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README.md
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The dataset consists of 2564 manually annotated tweets related to COVID-19 vaccines. The dataset can be used to discover the attitude expressed in the tweet towards the subject of COVID-19 vaccines. Tweets are in English. The dataset was curated in such a way as to maximize the likelihood of tweets with a strong emotional tone. We have assumed the existence of three classes:
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- PRO (label 0): positive, the tweet unequivocally suggests support for getting vaccinated against COVID-19
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- NEUTRAL(label 1): the tweet is mostly informative, does not show emotions vs. presented information, contains strong positive or negative emotions but concerning politics (vaccine distribution, vaccine passports, etc.)
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- AGAINST(label 2): the tweet is clearly against vaccination and contains warnings, conspiracy theories, etc.
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The dataset does not contain the content of Twitter statuses. Original tweets can be obtained via Twitter API.
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The dataset consists of 2564 manually annotated tweets related to COVID-19 vaccines. The dataset can be used to discover the attitude expressed in the tweet towards the subject of COVID-19 vaccines. Tweets are in English. The dataset was curated in such a way as to maximize the likelihood of tweets with a strong emotional tone. We have assumed the existence of three classes:
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- PRO (label 0): positive, the tweet unequivocally suggests support for getting vaccinated against COVID-19
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- NEUTRAL (label 1): the tweet is mostly informative, does not show emotions vs. presented information, contains strong positive or negative emotions but concerning politics (vaccine distribution, vaccine passports, etc.)
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- AGAINST (label 2): the tweet is clearly against vaccination and contains warnings, conspiracy theories, etc.
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The dataset does not contain the content of Twitter statuses. Original tweets can be obtained via Twitter API.
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