172 related articles for article (PubMed ID: 35639371)
1. Social Sharing of Emotion During the COVID-19 Pandemic.
Kim D; Park C; Kim E; Han J; Song H
Cyberpsychol Behav Soc Netw; 2022 Jun; 25(6):369-376. PubMed ID: 35639371
[TBL] [Abstract][Full Text] [Related]
2. Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence.
Adikari A; Nawaratne R; De Silva D; Ranasinghe S; Alahakoon O; Alahakoon D
J Med Internet Res; 2021 Apr; 23(4):e27341. PubMed ID: 33819167
[TBL] [Abstract][Full Text] [Related]
3. Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study.
Altan H; Coşgun A
BMC Oral Health; 2021 Aug; 21(1):418. PubMed ID: 34433449
[TBL] [Abstract][Full Text] [Related]
4. Emotional effect of the Covid-19 pandemic on oral surgery procedures: a social media analysis.
Altan A
J Dent Anesth Pain Med; 2021 Jun; 21(3):237-244. PubMed ID: 34136645
[TBL] [Abstract][Full Text] [Related]
5. Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends.
Lwin MO; Lu J; Sheldenkar A; Schulz PJ; Shin W; Gupta R; Yang Y
JMIR Public Health Surveill; 2020 May; 6(2):e19447. PubMed ID: 32412418
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Increased Online Aggression During COVID-19 Lockdowns: Two-Stage Study of Deep Text Mining and Difference-in-Differences Analysis.
Hsu JT; Tsai RT
J Med Internet Res; 2022 Aug; 24(8):e38776. PubMed ID: 35943771
[TBL] [Abstract][Full Text] [Related]
8. Trends of fear and anger on YouTube during the initial stage of the COVID-19 outbreak in South Korea.
Lee JJ; Kim J; Lee SK
BMC Public Health; 2024 Jun; 24(1):1496. PubMed ID: 38835010
[TBL] [Abstract][Full Text] [Related]
9. Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data.
Ng JY; Abdelkader W; Lokker C
BMC Complement Med Ther; 2022 Apr; 22(1):105. PubMed ID: 35418205
[TBL] [Abstract][Full Text] [Related]
10. Anxiety and Panic Buying Behaviour during COVID-19 Pandemic-A Qualitative Analysis of Toilet Paper Hoarding Contents on Twitter.
Leung J; Chung JYC; Tisdale C; Chiu V; Lim CCW; Chan G
Int J Environ Res Public Health; 2021 Jan; 18(3):. PubMed ID: 33514049
[No Abstract] [Full Text] [Related]
11. Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach.
Xue J; Chen J; Hu R; Chen C; Zheng C; Su Y; Zhu T
J Med Internet Res; 2020 Nov; 22(11):e20550. PubMed ID: 33119535
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. How Italy Tweeted about COVID-19: Detecting Reactions to the Pandemic from Social Media.
Lorenzoni V; Andreozzi G; Bazzani A; Casigliani V; Pirri S; Tavoschi L; Turchetti G
Int J Environ Res Public Health; 2022 Jun; 19(13):. PubMed ID: 35805444
[TBL] [Abstract][Full Text] [Related]
14. Using Twitter Comments to Understand People's Experiences of UK Health Care During the COVID-19 Pandemic: Thematic and Sentiment Analysis.
Ainley E; Witwicki C; Tallett A; Graham C
J Med Internet Res; 2021 Oct; 23(10):e31101. PubMed ID: 34469327
[TBL] [Abstract][Full Text] [Related]
15. Public perceptions about nurses communicated via Twitter in Turkey.
Şahan S; Yıldız A; Ergin E
Public Health Nurs; 2022 May; 39(3):638-642. PubMed ID: 34706103
[TBL] [Abstract][Full Text] [Related]
16. Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study.
Zhang C; Xu S; Li Z; Hu S
J Med Internet Res; 2021 Mar; 23(3):e26482. PubMed ID: 33617460
[TBL] [Abstract][Full Text] [Related]
17. Analysis of social media data for public emotion on the Wuhan lockdown event during the COVID-19 pandemic.
Cao G; Shen L; Evans R; Zhang Z; Bi Q; Huang W; Yao R; Zhang W
Comput Methods Programs Biomed; 2021 Nov; 212():106468. PubMed ID: 34715513
[TBL] [Abstract][Full Text] [Related]
18. The Resurgence of Cyber Racism During the COVID-19 Pandemic and its Aftereffects: Analysis of Sentiments and Emotions in Tweets.
Dubey AD
JMIR Public Health Surveill; 2020 Oct; 6(4):e19833. PubMed ID: 32936772
[TBL] [Abstract][Full Text] [Related]
19. Emotional Tone, Analytical Thinking, and Somatosensory Processes of a Sample of Italian Tweets During the First Phases of the COVID-19 Pandemic: Observational Study.
Monzani D; Vergani L; Pizzoli SFM; Marton G; Pravettoni G
J Med Internet Res; 2021 Oct; 23(10):e29820. PubMed ID: 34516386
[TBL] [Abstract][Full Text] [Related]
20. Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis.
Kwon J; Grady C; Feliciano JT; Fodeh SJ
J Biomed Inform; 2020 Nov; 111():103601. PubMed ID: 33065264
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
