{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T16:18:55Z","timestamp":1776442735054,"version":"3.51.2"},"reference-count":64,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T00:00:00Z","timestamp":1685318400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Universidad del Magdalena","award":["VIN 2022117"],"award-info":[{"award-number":["VIN 2022117"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>The COVID-19 pandemic has had a significant impact on various aspects of society, including economic, health, political, and work-related domains. The pandemic has also caused an emotional effect on individuals, reflected in their opinions and comments on social media platforms, such as Twitter. This study explores the evolution of sentiment in Spanish pandemic tweets through a data analysis based on a fine-tuned BERT architecture. A total of six million tweets were collected using web scraping techniques, and pre-processing was applied to filter and clean the data. The fine-tuned BERT architecture was utilized to perform sentiment analysis, which allowed for a deep-learning approach to sentiment classification. The analysis results were graphically represented based on search criteria, such as \u201cCOVID-19\u201d and \u201ccoronavirus\u201d. This study reveals sentiment trends, significant concerns, relationship with announced news, public reactions, and information dissemination, among other aspects. These findings provide insight into the emotional impact of the COVID-19 pandemic on individuals and the corresponding impact on social media platforms.<\/jats:p>","DOI":"10.3390\/data8060096","type":"journal-article","created":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T07:54:16Z","timestamp":1685346856000},"page":"96","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Exploring the Evolution of Sentiment in Spanish Pandemic Tweets: A Data Analysis Based on a Fine-Tuned BERT Architecture"],"prefix":"10.3390","volume":"8","author":[{"given":"Carlos Henr\u00edquez","family":"Miranda","sequence":"first","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad del Magdalena; Santa Marta 470001, Colombia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9069-0732","authenticated-orcid":false,"given":"German","family":"Sanchez-Torres","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad del Magdalena; Santa Marta 470001, Colombia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3762-8462","authenticated-orcid":false,"given":"Dixon","family":"Salcedo","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Electronics, University of the Coast, Barranquilla 080020, Colombia"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3022008","DOI":"10.17061\/phrp3022008","article-title":"How the COVID-19 Pandemic Is Focusing Attention on Loneliness and Social Isolation","volume":"30","author":"Smith","year":"2020","journal-title":"Public Health Res. 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