{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Kim Y"],"funding":["National Cancer Institute","NCI NIH HHS"],"pagination":["137-146"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7907568"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["30(2)"],"pubmed_abstract":["<h4>Background</h4>Electronic nicotine delivery systems (ENDS) are the most-used tobacco product by adolescents, and Juul has rapidly become the most popular ENDS brand. Evidence indicates that Juul has been marketed heavily on social media. In light of recent lawsuits against the FDA spurred by claims that the agency responded inadequately to this marketing push, measuring the social media conversation about ENDS like Juul has important public health implications.<h4>Methods</h4>We employed search filters to collect Juul-related and other ENDS-related data from Twitter in 2017-2018 using Gnip Historic PowerTrack. Trained coders labelled random samples for Juul and ENDS relevance, and the labelled samples were used to train a supervised learning classifier to filter out irrelevant tweets. "],"journal":["Tobacco control"],"pubmed_title":["At the speed of Juul: measuring the Twitter conversation related to ENDS and Juul across space and time (2017-2018)."],"pmcid":["PMC7907568"],"funding_grant_id":["R01CA194681-04S1","R01 CA194681"],"pubmed_authors":["Huang J","Kim Y","Emery SL","David B","Vera L"],"additional_accession":[]},"is_claimable":false,"name":"At the speed of Juul: measuring the Twitter conversation related to ENDS and Juul across space and time (2017-2018).","description":"<h4>Background</h4>Electronic nicotine delivery systems (ENDS) are the most-used tobacco product by adolescents, and Juul has rapidly become the most popular ENDS brand. Evidence indicates that Juul has been marketed heavily on social media. In light of recent lawsuits against the FDA spurred by claims that the agency responded inadequately to this marketing push, measuring the social media conversation about ENDS like Juul has important public health implications.<h4>Methods</h4>We employed search filters to collect Juul-related and other ENDS-related data from Twitter in 2017-2018 using Gnip Historic PowerTrack. Trained coders labelled random samples for Juul and ENDS relevance, and the labelled samples were used to train a supervised learning classifier to filter out irrelevant tweets. ","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Mar","modification":"2026-07-16T00:34:28.802Z","creation":"2026-07-09T13:10:11.804Z"},"accession":"S-EPMC7907568","cross_references":{"pubmed":["32198278"],"doi":["10.1136/tobaccocontrol-2019-055427"]}}