A Review of Models for Hydrating Large-scale Twitter Data of COVID-19-related Tweets for Transportation Research
<|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:'In response to the Coronavirus disease (COVID-19) outbreak and the Transportation Research Board’s (TRB) urgent need for work related to transportation and pandemics, this paper contributes with a sense of urgency and provides a starting point for research on the topic. The main goal of this paper is to support transportation researchers and the TRB community during this COVID-19 pandemic by reviewing the performance of software models used for extracting large-scale data from Twitter streams related to COVID-19. The study extends the previous research efforts in social media data mining by providing a review of contemporary tools, including their computing maturity and their potential usefulness. The paper also includes an open repository for the processed data frames to facilitate the quick development of new transportation research s' . 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 Pandemic, Twitter Data, Machine Learning, NLP, Social Media Mining"]} <|eot_id|>
 Here is the Description of a dataset. Description:'In response to the Coronavirus disease (COVID-19) outbreak and the Transportation Research Board’s (TRB) urgent need for work related to transportation and pandemics, this paper contributes with a sense of urgency and provides a starting point for research on the topic. The main goal of this paper is to support transportation researchers and the TRB community during this COVID-19 pandemic by reviewing the performance of software models used for extracting large-scale data from Twitter streams related to COVID-19. The study extends the previous research efforts in social media data mining by providing a review of contemporary tools, including their computing maturity and their potential usefulness. The paper also includes an open repository for the processed data frames to facilitate the quick development of new transportation research s' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
In response to the Coronavirus disease (COVID-19) outbreak and the Transportation Research Board’s (TRB) urgent need for work related to transportation and pandemics, this paper contributes with a sense of urgency and provides a starting point for research on the topic. The main goal of this paper is to support transportation researchers and the TRB community during this COVID-19 pandemic by reviewing the performance of software models used for extracting large-scale data from Twitter streams related to COVID-19. The study extends the previous research efforts in social media data mining by providing a review of contemporary tools, including their computing maturity and their potential usefulness. The paper also includes an open repository for the processed data frames to facilitate the quick development of new transportation research s
COVID-19 Pandemic, Twitter Data, Machine Learning, NLP, Social Media Mining