411 related articles for article (PubMed ID: 32570514)
1. Analysing Sentiment and Topics Related to Multiple Sclerosis on Twitter.
Giunti G; Claes M; Dorronzoro Zubiete E; Rivera-Romero O; Gabarron E
Stud Health Technol Inform; 2020 Jun; 270():911-915. PubMed ID: 32570514
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Mpox Panic, Infodemic, and Stigmatization of the Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual Community: Geospatial Analysis, Topic Modeling, and Sentiment Analysis of a Large, Multilingual Social Media Database.
Movahedi Nia Z; Bragazzi N; Asgary A; Orbinski J; Wu J; Kong J
J Med Internet Res; 2023 May; 25():e45108. PubMed ID: 37126377
[TBL] [Abstract][Full Text] [Related]
4. Impact of COVID-19 on Multiple Sclerosis Topic Discussion on Twitter.
Giunti G; Claes M; Zubiete ED; Rivera-Romero O; Gabarron E
Stud Health Technol Inform; 2021 May; 281():865-869. PubMed ID: 34042797
[TBL] [Abstract][Full Text] [Related]
5. Identifying Key Topics Bearing Negative Sentiment on Twitter: Insights Concerning the 2015-2016 Zika Epidemic.
Mamidi R; Miller M; Banerjee T; Romine W; Sheth A
JMIR Public Health Surveill; 2019 Jun; 5(2):e11036. PubMed ID: 31165711
[TBL] [Abstract][Full Text] [Related]
6. Using Social Media Data to Understand the Impact of Promotional Information on Laypeople's Discussions: A Case Study of Lynch Syndrome.
Bian J; Zhao Y; Salloum RG; Guo Y; Wang M; Prosperi M; Zhang H; Du X; Ramirez-Diaz LJ; He Z; Sun Y
J Med Internet Res; 2017 Dec; 19(12):e414. PubMed ID: 29237586
[TBL] [Abstract][Full Text] [Related]
7. Stroke Survivors on Twitter: Sentiment and Topic Analysis From a Gender Perspective.
Garcia-Rudolph A; Laxe S; Saurí J; Bernabeu Guitart M
J Med Internet Res; 2019 Aug; 21(8):e14077. PubMed ID: 31452514
[TBL] [Abstract][Full Text] [Related]
8. Using Natural Language Processing to Explore Social Media Opinions on Food Security: Sentiment Analysis and Topic Modeling Study.
Molenaar A; Lukose D; Brennan L; Jenkins EL; McCaffrey TA
J Med Internet Res; 2024 Mar; 26():e47826. PubMed ID: 38512326
[TBL] [Abstract][Full Text] [Related]
9. Geographic Differences in Cannabis Conversations on Twitter: Infodemiology Study.
van Draanen J; Tao H; Gupta S; Liu S
JMIR Public Health Surveill; 2020 Oct; 6(4):e18540. PubMed ID: 33016888
[TBL] [Abstract][Full Text] [Related]
10. Diabetes on Twitter: A Sentiment Analysis.
Gabarron E; Dorronzoro E; Rivera-Romero O; Wynn R
J Diabetes Sci Technol; 2019 May; 13(3):439-444. PubMed ID: 30453762
[TBL] [Abstract][Full Text] [Related]
11. Social media analysis of Twitter tweets related to ASD in 2019-2020, with particular attention to COVID-19: topic modelling and sentiment analysis.
Corti L; Zanetti M; Tricella G; Bonati M
J Big Data; 2022; 9(1):113. PubMed ID: 36465137
[TBL] [Abstract][Full Text] [Related]
12. Applying Multiple Data Collection Tools to Quantify Human Papillomavirus Vaccine Communication on Twitter.
Massey PM; Leader A; Yom-Tov E; Budenz A; Fisher K; Klassen AC
J Med Internet Res; 2016 Dec; 18(12):e318. PubMed ID: 27919863
[TBL] [Abstract][Full Text] [Related]
13. Public attitudes toward COVID-19 vaccines on English-language Twitter: A sentiment analysis.
Liu S; Liu J
Vaccine; 2021 Sep; 39(39):5499-5505. PubMed ID: 34452774
[TBL] [Abstract][Full Text] [Related]
14. Using Twitter to Understand the Human Bowel Disease Community: Exploratory Analysis of Key Topics.
Pérez-Pérez M; Pérez-Rodríguez G; Fdez-Riverola F; Lourenço A
J Med Internet Res; 2019 Aug; 21(8):e12610. PubMed ID: 31411142
[TBL] [Abstract][Full Text] [Related]
15. Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study.
Boon-Itt S; Skunkan Y
JMIR Public Health Surveill; 2020 Nov; 6(4):e21978. PubMed ID: 33108310
[TBL] [Abstract][Full Text] [Related]
16. Perceptions of Menthol Cigarettes Among Twitter Users: Content and Sentiment Analysis.
Rose SW; Jo CL; Binns S; Buenger M; Emery S; Ribisl KM
J Med Internet Res; 2017 Feb; 19(2):e56. PubMed ID: 28242592
[TBL] [Abstract][Full Text] [Related]
17. Mapping Individual Differences on the Internet: Case Study of the Type 1 Diabetes Community.
Bedford-Petersen C; Weston SJ
JMIR Diabetes; 2021 Oct; 6(4):e30756. PubMed ID: 34652277
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Using Social Media to Characterize Public Sentiment Toward Medical Interventions Commonly Used for Cancer Screening: An Observational Study.
Metwally O; Blumberg S; Ladabaum U; Sinha SR
J Med Internet Res; 2017 Jun; 19(6):e200. PubMed ID: 28592395
[TBL] [Abstract][Full Text] [Related]
20. Population attitudes toward contraceptive methods over time on a social media platform.
Merz AA; Gutiérrez-Sacristán A; Bartz D; Williams NE; Ojo A; Schaefer KM; Huang M; Li CY; Sandoval RS; Ye S; Cathcart AM; Starosta A; Avillach P
Am J Obstet Gynecol; 2021 Jun; 224(6):597.e1-597.e14. PubMed ID: 33309562
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
