A Sentiment Analysis of Turkish Tweets Shared in Nursing Week During the Pandemic
| dc.authorscopusid | 57215683950 | |
| dc.authorscopusid | 58082138500 | |
| dc.authorscopusid | 57056407400 | |
| dc.contributor.author | Doğan, M.B. | |
| dc.contributor.author | Oban, V. | |
| dc.contributor.author | Dikeç, G. | |
| dc.date.accessioned | 2025-04-11T19:31:06Z | |
| dc.date.available | 2025-04-11T19:31:06Z | |
| dc.date.issued | 2022 | |
| dc.department | Fenerbahçe University | en_US |
| dc.department-temp | Doğan M.B., Arel University, Faculty of Health Sciences, Department of Nursing, Istanbul, Türkiye; Oban V., Istinye University, Faculty of Fine Arts, Design and Architecture, Department of Digital Game Design, Istanbul, Türkiye; Dikeç G., Fenerbahce University, Faculty of Health Sciences, Department of Nursing, Istanbul, Türkiye | en_US |
| dc.description.abstract | Aim: This study aimed to conduct an artificial intelligence-based sentiment analysis of Turkish tweets about nursing during the nursing week during the COVID-19 pandemic. Method: This is a retrospective descriptive survey. Between May 4 and May 19, 2021, Turkish tweets were analyzed using the Python library Tweepy. The search terms “nurse, nursing, and nursing week” were used to analyzed tweets for their positivity, neutrality, or negativity. Results: The analysis of 24,944 tweets revealed that tweets frequently express neutral emotions. The negative tweets frequently discussed issues such as societal gender perception, professionalism, burnout during the pandemic, salaries, inadequate nursing workforce, inequalities, violence against healthcare professionals, and the deaths of nurses. Conclusions: Social media applications can be recommended as important tools for raising awareness of the nursing profession identity, professionalism, visibility, and the perception of society towards nursing, nursing problems, and recommendations for solutions. © 2022 The Authors. Published by Association of Nurse Managers. | en_US |
| dc.description.sponsorship | UK Research and Innovation, UKRI, (103637) | en_US |
| dc.identifier.doi | 10.54304/SHYD.2022.20053 | |
| dc.identifier.endpage | 238 | en_US |
| dc.identifier.issn | 2149-018X | |
| dc.identifier.issue | 2 | en_US |
| dc.identifier.scopus | 2-s2.0-85169469048 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 230 | en_US |
| dc.identifier.uri | https://doi.org/10.54304/SHYD.2022.20053 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14627/907 | |
| dc.identifier.volume | 9 | en_US |
| dc.identifier.wosquality | N/A | |
| dc.language.iso | en | en_US |
| dc.publisher | Association of Executive Nurses | en_US |
| dc.relation.ispartof | Journal of Health and Nursing Management | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.scopus.citedbyCount | 1 | |
| dc.subject | Artificial Intelligence | en_US |
| dc.subject | Natural Language Processing | en_US |
| dc.subject | Nursing | en_US |
| dc.subject | Social Media | en_US |
| dc.title | A Sentiment Analysis of Turkish Tweets Shared in Nursing Week During the Pandemic | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication |