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Folly Beach Library
9 a.m. - 5:30 p.m.
Phone: (843) 588-2001
Edgar Allan Poe/Sullivan's Island Library
Closed for renovations
Phone: (843) 883-3914
West Ashley Library
9 a.m. – 7 p.m.
Phone: (843) 766-6635
Wando Mount Pleasant Library
9 a.m. – 8 p.m.
Phone: (843) 805-6888
Village Library
9 a.m. - 6 p.m.
Phone: (843) 884-9741
St. Paul's/Hollywood Library
9 a.m. – 8 p.m.
Phone: (843) 889-3300
Otranto Road Library
9 a.m. – 8 p.m.
Phone: (843) 572-4094
Mt. Pleasant Library
9 a.m. – 8 p.m.
Phone: (843) 849-6161
McClellanville Library
9 a.m. - 6 p.m.
Phone: (843) 887-3699
Keith Summey North Charleston Library
9 a.m. – 8 p.m.
Phone: (843) 744-2489
John's Island Library
9 a.m. – 8 p.m.
Phone: (843) 559-1945
Hurd/St. Andrews Library
9 a.m. – 8 p.m.
Phone: (843) 766-2546
Miss Jane's Building (Edisto Library Temporary Location)
9 a.m. - 4 p.m.
Phone: (843) 869-2355
Dorchester Road Library
9 a.m. – 8 p.m.
Phone: (843) 552-6466
John L. Dart Library
9 a.m. – 7 p.m.
Phone: (843) 722-7550
Baxter-Patrick James Island
9 a.m. – 8 p.m.
Phone: (843) 795-6679
Main Library
9 a.m. – 8 p.m.
Phone: (843) 805-6930
Bees Ferry West Ashley Library
9 a.m. – 8 p.m.
Phone: (843) 805-6892
Mobile Library
9 a.m. - 5 p.m.
Phone: (843) 805-6909
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Unmasking People's Opinions behind Mask-Wearing during COVID-19 Pandemic—A Twitter Stance Analysis.
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![loading](/sites/all/modules/hf_eds/images/loading.gif)
- Author(s): Cotfas, Liviu-Adrian; Delcea, Camelia; Gherai, Rareș; Roxin, Ioan
- Source:
Symmetry (20738994); Nov2021, Vol. 13 Issue 11, p1995, 1p- Subject Terms:
- Source:
- Additional Information
- Abstract: Wearing a mask by the general public has been a controversial issue from the beginning of the COVID-19 pandemic as the public authorities have had mixed messages, either advising people not to wear masks if uninfected, to wear as a protective measure, to wear them only when inside a building/room with insufficient air flow or to wear them in all the public places. To date, the governments have had different policies regarding mask-wearing by the general public depending on the COVID-19 pandemic evolution. In this context, the paper analyzes the general public's opinion regarding mask-wearing for the one-year period starting from 9 January 2020, when the first tweet regarding mask-wearing in the COVID-19 context has been posted. Classical machine learning and deep learning algorithms have been considered in analyzing the 8,795,633 tweets extracted. A random sample of 29,613 tweets has been extracted and annotated. The tweets containing news and information related to mask-wearing have been included in the neutral category, while the ones containing people's opinions (for or against) have been marked using a symmetrical approach into in favor and against categories. Based on the analysis, it has been determined that most of the mask tweets are in the area of in favor or neutral, while a smaller percentage of tweets and retweets are in the against category. The evolution of the opinions expressed through tweets can be further monitored for extracting the public perspective on mask-wearing in times of COVID-19. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Symmetry (20738994) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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