These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
460 related articles for article (PubMed ID: 32986469)
1. Whose Tweets on COVID-19 Gain the Most Attention: Celebrities, Political, or Scientific Authorities? Kamiński M; Szymańska C; Nowak JK Cyberpsychol Behav Soc Netw; 2021 Feb; 24(2):123-128. PubMed ID: 32986469 [TBL] [Abstract][Full Text] [Related]
2. Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study. Abd-Alrazaq A; Alhuwail D; Househ M; Hamdi M; Shah Z J Med Internet Res; 2020 Apr; 22(4):e19016. PubMed ID: 32287039 [TBL] [Abstract][Full Text] [Related]
3. Smoking, Vaping, and Tobacco Industry During COVID-19 Pandemic: Twitter Data Analysis. Kamiński M; Muth A; Bogdański P Cyberpsychol Behav Soc Netw; 2020 Dec; 23(12):811-817. PubMed ID: 32757951 [TBL] [Abstract][Full Text] [Related]
4. The Saudi Ministry of Health's Twitter Communication Strategies and Public Engagement During the COVID-19 Pandemic: Content Analysis Study. Alhassan FM; AlDossary SA JMIR Public Health Surveill; 2021 Jul; 7(7):e27942. PubMed ID: 34117860 [TBL] [Abstract][Full Text] [Related]
5. Examining Tweet Content and Engagement of Canadian Public Health Agencies and Decision Makers During COVID-19: Mixed Methods Analysis. Slavik CE; Buttle C; Sturrock SL; Darlington JC; Yiannakoulias N J Med Internet Res; 2021 Mar; 23(3):e24883. PubMed ID: 33651705 [TBL] [Abstract][Full Text] [Related]
6. Language and Sentiment Regarding Telemedicine and COVID-19 on Twitter: Longitudinal Infodemiology Study. Pollack CC; Gilbert-Diamond D; Alford-Teaster JA; Onega T J Med Internet Res; 2021 Jun; 23(6):e28648. PubMed ID: 34086591 [TBL] [Abstract][Full Text] [Related]
7. Topics, Trends, and Sentiments of Tweets About the COVID-19 Pandemic: Temporal Infoveillance Study. Chandrasekaran R; Mehta V; Valkunde T; Moustakas E J Med Internet Res; 2020 Oct; 22(10):e22624. PubMed ID: 33006937 [TBL] [Abstract][Full Text] [Related]
8. The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis. Drescher LS; Roosen J; Aue K; Dressel K; Schär W; Götz A JMIR Public Health Surveill; 2021 Dec; 7(12):e31834. PubMed ID: 34710054 [TBL] [Abstract][Full Text] [Related]
9. Qualitative analysis of visual risk communication on twitter during the Covid-19 pandemic. Sleigh J; Amann J; Schneider M; Vayena E BMC Public Health; 2021 Apr; 21(1):810. PubMed ID: 33906626 [TBL] [Abstract][Full Text] [Related]
10. Factors Driving the Popularity and Virality of COVID-19 Vaccine Discourse on Twitter: Text Mining and Data Visualization Study. Zhang J; Wang Y; Shi M; Wang X JMIR Public Health Surveill; 2021 Dec; 7(12):e32814. PubMed ID: 34665761 [TBL] [Abstract][Full Text] [Related]
11. World leaders' usage of Twitter in response to the COVID-19 pandemic: a content analysis. Rufai SR; Bunce C J Public Health (Oxf); 2020 Aug; 42(3):510-516. PubMed ID: 32309854 [TBL] [Abstract][Full Text] [Related]
12. Sentiment Analysis of Twitter Posts Related to a COVID-19 Test & Trace Program in NYC. Tsai KA; Chau MM; Wang J; Thorpe LE; Massar RE; Conderino S; Berry CA; Islam NS; Bershteyn A; Bragg MA J Urban Health; 2024 Oct; 101(5):898-901. PubMed ID: 39325247 [TBL] [Abstract][Full Text] [Related]
13. Texas Public Agencies' Tweets and Public Engagement During the COVID-19 Pandemic: Natural Language Processing Approach. Tang L; Liu W; Thomas B; Tran HTN; Zou W; Zhang X; Zhi D JMIR Public Health Surveill; 2021 Apr; 7(4):e26720. PubMed ID: 33847587 [TBL] [Abstract][Full Text] [Related]
14. General Surgery Twitter during COVID-19: Tweets, Trends, and Implications for Recruitment Strategies. Cox JS; Wehrle CJ; Mejias C; Devarakonda AK; McKenzie JA; Arora TK Am Surg; 2023 May; 89(5):1504-1511. PubMed ID: 34937400 [TBL] [Abstract][Full Text] [Related]
15. Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence. Hung M; Lauren E; Hon ES; Birmingham WC; Xu J; Su S; Hon SD; Park J; Dang P; Lipsky MS J Med Internet Res; 2020 Aug; 22(8):e22590. PubMed ID: 32750001 [TBL] [Abstract][Full Text] [Related]
16. Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the "Chinese virus" on Twitter: Quantitative Analysis of Social Media Data. Budhwani H; Sun R J Med Internet Res; 2020 May; 22(5):e19301. PubMed ID: 32343669 [TBL] [Abstract][Full Text] [Related]
17. Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19-Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study. Pobiruchin M; Zowalla R; Wiesner M J Med Internet Res; 2020 Aug; 22(8):e19629. PubMed ID: 32790641 [TBL] [Abstract][Full Text] [Related]
18. Misinformation about spinal manipulation and boosting immunity: an analysis of Twitter activity during the COVID-19 crisis. Kawchuk G; Hartvigsen J; Harsted S; Nim CG; Nyirö L Chiropr Man Therap; 2020 Jun; 28(1):34. PubMed ID: 32517803 [TBL] [Abstract][Full Text] [Related]
19. Emotion diffusion effect: Negative sentiment COVID-19 tweets of public organizations attract more responses from followers. Yu H; Yang CC; Yu P; Liu K PLoS One; 2022; 17(3):e0264794. PubMed ID: 35259181 [TBL] [Abstract][Full Text] [Related]
20. Content and User Engagement of Health-Related Behavior Tweets Posted by Mass Media Outlets From Spain and the United States Early in the COVID-19 Pandemic: Observational Infodemiology Study. Alvarez-Mon MA; Pereira-Sanchez V; Hooker ER; Sanchez F; Alvarez-Mon M; Teo AR JMIR Infodemiology; 2023 Aug; 3():e43685. PubMed ID: 37347948 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]