COVID-19 Mask Use Geocoded Twitter Data - Nov. 2020
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Data collection was conducted through an open-sourced Twitter scraper built by the researchers using the Twitter API and the Python library Tweepy and consisted of periodic data grabs over a 30-day period between November 1-30, 2020. The data collection was based on the terms masksdontwork, kungflu, scamdemic, plandemic, Hydroxychloroquine, Chinavirus, Chinesevirus, and herdimmunity, which were observed to be popular among the conservative users who engage with COVID-19-related content on Twitter prior to data collection. Data include both hashtags and keywords/phrases included in the tweet text. The data collection yielded 25,152 geocoded tweets in the study timeframe' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["COVID-19","Geocode","Twitter"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Data collection was conducted through an open-sourced Twitter scraper built by the researchers using the Twitter API and the Python library Tweepy and consisted of periodic data grabs over a 30-day period between November 1-30, 2020. The data collection was based on the terms masksdontwork, kungflu, scamdemic, plandemic, Hydroxychloroquine, Chinavirus, Chinesevirus, and herdimmunity, which were observed to be popular among the conservative users who engage with COVID-19-related content on Twitter prior to data collection. Data include both hashtags and keywords/phrases included in the tweet text. The data collection yielded 25,152 geocoded tweets in the study timeframe' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Data collection was conducted through an open-sourced Twitter scraper built by the researchers using the Twitter API and the Python library Tweepy and consisted of periodic data grabs over a 30-day period between November 1-30, 2020. The data collection was based on the terms masksdontwork, kungflu, scamdemic, plandemic, Hydroxychloroquine, Chinavirus, Chinesevirus, and herdimmunity, which were observed to be popular among the conservative users who engage with COVID-19-related content on Twitter prior to data collection. Data include both hashtags and keywords/phrases included in the tweet text. The data collection yielded 25,152 geocoded tweets in the study timeframe
COVID-19; Geocode; Twitter