190 related articles for article (PubMed ID: 37358808)
1. Examining the Prevailing Negative Sentiments Surrounding Measles Vaccination: Unsupervised Deep Learning of Twitter Posts from 2017 to 2022.
Ng QX; Teo YQJ; Kiew CY; Lim BP; Lim YL; Liew TM
Cyberpsychol Behav Soc Netw; 2023 Aug; 26(8):621-630. PubMed ID: 37358808
[TBL] [Abstract][Full Text] [Related]
2. Examining the Prevailing Negative Sentiments Related to COVID-19 Vaccination: Unsupervised Deep Learning of Twitter Posts over a 16 Month Period.
Ng QX; Lim SR; Yau CE; Liew TM
Vaccines (Basel); 2022 Sep; 10(9):. PubMed ID: 36146535
[TBL] [Abstract][Full Text] [Related]
3. Examining the Negative Sentiments Related to Influenza Vaccination from 2017 to 2022: An Unsupervised Deep Learning Analysis of 261,613 Twitter Posts.
Ng QX; Lee DYX; Ng CX; Yau CE; Lim YL; Liew TM
Vaccines (Basel); 2023 May; 11(6):. PubMed ID: 37376407
[TBL] [Abstract][Full Text] [Related]
4. Examining the Utility of Social Media in COVID-19 Vaccination: Unsupervised Learning of 672,133 Twitter Posts.
Liew TM; Lee CS
JMIR Public Health Surveill; 2021 Nov; 7(11):e29789. PubMed ID: 34583316
[TBL] [Abstract][Full Text] [Related]
5. Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis.
Jang H; Rempel E; Roe I; Adu P; Carenini G; Janjua NZ
J Med Internet Res; 2022 Mar; 24(3):e35016. PubMed ID: 35275835
[TBL] [Abstract][Full Text] [Related]
6. Uncovering the Reasons Behind COVID-19 Vaccine Hesitancy in Serbia: Sentiment-Based Topic Modeling.
Ljajić A; Prodanović N; Medvecki D; Bašaragin B; Mitrović J
J Med Internet Res; 2022 Nov; 24(11):e42261. PubMed ID: 36301673
[TBL] [Abstract][Full Text] [Related]
7. Examining Public Sentiments and Attitudes Toward COVID-19 Vaccination: Infoveillance Study Using Twitter Posts.
Chandrasekaran R; Desai R; Shah H; Kumar V; Moustakas E
JMIR Infodemiology; 2022; 2(1):e33909. PubMed ID: 35462735
[TBL] [Abstract][Full Text] [Related]
8. Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis.
Kwok SWH; Vadde SK; Wang G
J Med Internet Res; 2021 May; 23(5):e26953. PubMed ID: 33886492
[TBL] [Abstract][Full Text] [Related]
9. Public sentiment on the global outbreak of monkeypox: an unsupervised machine learning analysis of 352,182 twitter posts.
Ng QX; Yau CE; Lim YL; Wong LKT; Liew TM
Public Health; 2022 Dec; 213():1-4. PubMed ID: 36308872
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Vaccine sentiment analysis using BERT + NBSVM and geo-spatial approaches.
Umair A; Masciari E; Ullah MH
J Supercomput; 2023 May; ():1-31. PubMed ID: 37359330
[TBL] [Abstract][Full Text] [Related]
12. Dynamics of the Negative Discourse Toward COVID-19 Vaccines: Topic Modeling Study and an Annotated Data Set of Twitter Posts.
Lindelöf G; Aledavood T; Keller B
J Med Internet Res; 2023 Apr; 25():e41319. PubMed ID: 36877804
[TBL] [Abstract][Full Text] [Related]
13. Public sentiments toward COVID-19 vaccines in South African cities: An analysis of Twitter posts.
Ogbuokiri B; Ahmadi A; Bragazzi NL; Movahedi Nia Z; Mellado B; Wu J; Orbinski J; Asgary A; Kong J
Front Public Health; 2022; 10():987376. PubMed ID: 36033735
[TBL] [Abstract][Full Text] [Related]
14. Topics and Sentiments of Public Concerns Regarding COVID-19 Vaccines: Social Media Trend Analysis.
Monselise M; Chang CH; Ferreira G; Yang R; Yang CC
J Med Internet Res; 2021 Oct; 23(10):e30765. PubMed ID: 34581682
[TBL] [Abstract][Full Text] [Related]
15. A Comprehensive Analysis of COVID-19 Vaccine Discourse by Vaccine Brand on Twitter in Korea: Topic and Sentiment Analysis.
Park S; Suh YK
J Med Internet Res; 2023 Jan; 25():e42623. PubMed ID: 36603153
[TBL] [Abstract][Full Text] [Related]
16. Social media sentiment analysis to monitor the performance of vaccination coverage during the early phase of the national COVID-19 vaccine rollout.
Rahmanti AR; Chien CH; Nursetyo AA; Husnayain A; Wiratama BS; Fuad A; Yang HC; Li YJ
Comput Methods Programs Biomed; 2022 Jun; 221():106838. PubMed ID: 35567863
[TBL] [Abstract][Full Text] [Related]
17. COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment-Based Topic Modeling.
Huangfu L; Mo Y; Zhang P; Zeng DD; He S
J Med Internet Res; 2022 Feb; 24(2):e31726. PubMed ID: 34783665
[TBL] [Abstract][Full Text] [Related]
18. Artificial Intelligence-Enabled Analysis of Public Attitudes on Facebook and Twitter Toward COVID-19 Vaccines in the United Kingdom and the United States: Observational Study.
Hussain A; Tahir A; Hussain Z; Sheikh Z; Gogate M; Dashtipour K; Ali A; Sheikh A
J Med Internet Res; 2021 Apr; 23(4):e26627. PubMed ID: 33724919
[TBL] [Abstract][Full Text] [Related]
19. Examining Rural and Urban Sentiment Difference in COVID-19-Related Topics on Twitter: Word Embedding-Based Retrospective Study.
Liu Y; Yin Z; Ni C; Yan C; Wan Z; Malin B
J Med Internet Res; 2023 Feb; 25():e42985. PubMed ID: 36790847
[TBL] [Abstract][Full Text] [Related]
20. HPV vaccine narratives on Twitter during the COVID-19 pandemic: a social network, thematic, and sentiment analysis.
Boucher JC; Kim SY; Jessiman-Perreault G; Edwards J; Smith H; Frenette N; Badami A; Scott LA
BMC Public Health; 2023 Apr; 23(1):694. PubMed ID: 37060069
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]