128 related articles for article (PubMed ID: 35837649)
1. Users' Feedback on COVID-19 Lockdown Documentary: An Emotion Analysis and Topic Modeling Analysis.
Shi X; Jia M; Li J; Chen Q; Liu G; Liu Q
Front Psychol; 2022; 13():944049. PubMed ID: 35837649
[TBL] [Abstract][Full Text] [Related]
2. Direct-to-Consumer Genetic Testing on Social Media: Topic Modeling and Sentiment Analysis of YouTube Users' Comments.
Toussaint PA; Renner M; Lins S; Thiebes S; Sunyaev A
JMIR Infodemiology; 2022; 2(2):e38749. PubMed ID: 37113449
[TBL] [Abstract][Full Text] [Related]
3. COVID-19 Vaccine-Related Discussion on Twitter: Topic Modeling and Sentiment Analysis.
Lyu JC; Han EL; Luli GK
J Med Internet Res; 2021 Jun; 23(6):e24435. PubMed ID: 34115608
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Emotional Attitudes of Chinese Citizens on Social Distancing During the COVID-19 Outbreak: Analysis of Social Media Data.
Shen L; Yao R; Zhang W; Evans R; Cao G; Zhang Z
JMIR Med Inform; 2021 Mar; 9(3):e27079. PubMed ID: 33724200
[TBL] [Abstract][Full Text] [Related]
6. Comparison of the Users' Attitudes Toward Cannabidiol on Social Media Platforms: Topic Modeling Study.
Li Y; Yan X; Wang Z; Ma M; Zhang B; Jia Z
JMIR Public Health Surveill; 2023 Jan; 9():e34132. PubMed ID: 36630175
[TBL] [Abstract][Full Text] [Related]
7. Concerns Expressed by Chinese Social Media Users During the COVID-19 Pandemic: Content Analysis of Sina Weibo Microblogging Data.
Wang J; Zhou Y; Zhang W; Evans R; Zhu C
J Med Internet Res; 2020 Nov; 22(11):e22152. PubMed ID: 33151894
[TBL] [Abstract][Full Text] [Related]
8. Public Opinions and Concerns Regarding the Canadian Prime Minister's Daily COVID-19 Briefing: Longitudinal Study of YouTube Comments Using Machine Learning Techniques.
Zheng C; Xue J; Sun Y; Zhu T
J Med Internet Res; 2021 Feb; 23(2):e23957. PubMed ID: 33544690
[TBL] [Abstract][Full Text] [Related]
9. Exploring Abnormal Behavior Patterns of Online Users With Emotional Eating Behavior: Topic Modeling Study.
Hwang Y; Kim HJ; Choi HJ; Lee J
J Med Internet Res; 2020 Mar; 22(3):e15700. PubMed ID: 32229461
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. Thematic Analysis on User Reviews for Depression and Anxiety Chatbot Apps: Machine Learning Approach.
Ahmed A; Aziz S; Khalifa M; Shah U; Hassan A; Abd-Alrazaq A; Househ M
JMIR Form Res; 2022 Mar; 6(3):e27654. PubMed ID: 35275069
[TBL] [Abstract][Full Text] [Related]
13. Beyond fear and anger: A global analysis of emotional response to Covid-19 news on Twitter using deep learning.
Oliveira FB; Mougouei D; Haque A; Sichman JS; Dam HK; Evans S; Ghose A; Singh MP
Online Soc Netw Media; 2023 Jun; ():100253. PubMed ID: 37360968
[TBL] [Abstract][Full Text] [Related]
14. The Emotional Anatomy of the Wuhan Lockdown: Sentiment Analysis Using Weibo Data.
Chen X; Yik M
JMIR Form Res; 2022 Nov; 6(11):e37698. PubMed ID: 36166650
[TBL] [Abstract][Full Text] [Related]
15. Real-Time Infoveillance of Moroccan Social Media Users' Sentiments towards the COVID-19 Pandemic and Its Management.
Ghanem A; Asaad C; Hafidi H; Moukafih Y; Guermah B; Sbihi N; Zakroum M; Ghogho M; Dairi M; Cherqaoui M; Baina K
Int J Environ Res Public Health; 2021 Nov; 18(22):. PubMed ID: 34831927
[TBL] [Abstract][Full Text] [Related]
16. Food for thought: A natural language processing analysis of the 2020 Dietary Guidelines publice comments.
Lindquist J; Thomas DM; Turner D; Blankenship J; Kyle TK
Am J Clin Nutr; 2021 Aug; 114(2):713-720. PubMed ID: 34134135
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube.
Obadimu A; Khaund T; Mead E; Marcoux T; Agarwal N
Inf Process Manag; 2021 Sep; 58(5):102660. PubMed ID: 36567973
[TBL] [Abstract][Full Text] [Related]
19. Comparing Public Sentiment Toward COVID-19 Vaccines Across Canadian Cities: Analysis of Comments on Reddit.
Yan C; Law M; Nguyen S; Cheung J; Kong J
J Med Internet Res; 2021 Sep; 23(9):e32685. PubMed ID: 34519654
[TBL] [Abstract][Full Text] [Related]
20. Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach.
Liu Q; Zheng Z; Zheng J; Chen Q; Liu G; Chen S; Chu B; Zhu H; Akinwunmi B; Huang J; Zhang CJP; Ming WK
J Med Internet Res; 2020 Apr; 22(4):e19118. PubMed ID: 32302966
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
