eprintid: 3483 rev_number: 11 eprint_status: archive userid: 2 dir: disk0/00/00/34/83 datestamp: 2022-09-06 17:30:03 lastmod: 2023-07-11 23:30:18 status_changed: 2022-09-06 17:30:03 type: article metadata_visibility: show creators_name: Qamar, Usman creators_name: Ahmad, Ayaz creators_name: Rustam, Furqan creators_name: Saad, Eysha creators_name: Siddique, Muhammad Abubakar creators_name: Lee, Ernesto creators_name: Ortega-Mansilla, Arturo creators_name: Díez, Isabel de la Torre creators_name: Ashraf, Imran creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: creators_id: arturo.ortega@uneatlantico.es creators_id: creators_id: title: Analyzing preventive precautions to limit spread of COVID-19 ispublished: pub subjects: uneat_eng divisions: uneatlantico_produccion_cientifica divisions: uninimx_produccion_cientifica full_text_status: public abstract: With the global spread of COVID-19, the governments advised the public for adopting safety precautions to limit its spread. The virus spreads from people, contaminated places, and nozzle droplets that necessitate strict precautionary measures. Consequently, different safety precautions have been implemented to fight COVID-19 such as wearing a facemask, restriction of social gatherings, keeping 6 feet distance, etc. Despite the warnings, highlighted need for such measures, and the increasing severity of the pandemic situation, the expected number of people adopting these precautions is low. This study aims at assessing and understanding the public perception of COVID-19 safety precautions, especially the use of facemask. A unified framework of sentiment lexicon with the proposed ensemble EB-DT is devised to analyze sentiments regarding safety precautions. Extensive experiments are performed with a large dataset collected from Twitter. In addition, the factors leading to a negative perception of safety precautions are analyzed by performing topic analysis using the Latent Dirichlet allocation algorithm. The experimental results reveal that 12% of the tweets correspond to negative sentiments towards facemask precaution mainly by its discomfort. Analysis of change in peoples’ sentiment over time indicates a gradual increase in the positive sentiments regarding COVID-19 restrictions. date: 2022-08 publication: PLOS ONE volume: 17 number: 8 pagerange: e0272350 id_number: doi:10.1371/journal.pone.0272350 refereed: TRUE issn: 1932-6203 official_url: http://doi.org/10.1371/journal.pone.0272350 access: open language: en citation: Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica Universidad Internacional Iberoamericana México > Investigación > Producción Científica Abierto Inglés With the global spread of COVID-19, the governments advised the public for adopting safety precautions to limit its spread. The virus spreads from people, contaminated places, and nozzle droplets that necessitate strict precautionary measures. Consequently, different safety precautions have been implemented to fight COVID-19 such as wearing a facemask, restriction of social gatherings, keeping 6 feet distance, etc. Despite the warnings, highlighted need for such measures, and the increasing severity of the pandemic situation, the expected number of people adopting these precautions is low. This study aims at assessing and understanding the public perception of COVID-19 safety precautions, especially the use of facemask. A unified framework of sentiment lexicon with the proposed ensemble EB-DT is devised to analyze sentiments regarding safety precautions. Extensive experiments are performed with a large dataset collected from Twitter. In addition, the factors leading to a negative perception of safety precautions are analyzed by performing topic analysis using the Latent Dirichlet allocation algorithm. The experimental results reveal that 12% of the tweets correspond to negative sentiments towards facemask precaution mainly by its discomfort. Analysis of change in peoples’ sentiment over time indicates a gradual increase in the positive sentiments regarding COVID-19 restrictions. metadata Qamar, Usman; Ahmad, Ayaz; Rustam, Furqan; Saad, Eysha; Siddique, Muhammad Abubakar; Lee, Ernesto; Ortega-Mansilla, Arturo; Díez, Isabel de la Torre y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, arturo.ortega@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) Analyzing preventive precautions to limit spread of COVID-19. PLOS ONE, 17 (8). e0272350. ISSN 1932-6203 document_url: http://repositorio.unini.edu.mx/id/eprint/3483/1/journal.pone.0272350.pdf