217 related articles for article (PubMed ID: 29470166)
1. What Drives Health Professionals to Tweet About #HPVvaccine? Identifying Strategies for Effective Communication.
Massey PM; Budenz A; Leader A; Fisher K; Klassen AC; Yom-Tov E
Prev Chronic Dis; 2018 Feb; 15():E26. PubMed ID: 29470166
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. A Cross-Sectional Review of Cervical Cancer Messages on Twitter During Cervical Cancer Awareness Month.
Teoh D; Shaikh R; Vogel RI; Zoellner T; Carson L; Kulasingam S; Lou E
J Low Genit Tract Dis; 2018 Jan; 22(1):8-12. PubMed ID: 29271850
[TBL] [Abstract][Full Text] [Related]
4. Leveraging machine learning-based approaches to assess human papillomavirus vaccination sentiment trends with Twitter data.
Du J; Xu J; Song HY; Tao C
BMC Med Inform Decis Mak; 2017 Jul; 17(Suppl 2):69. PubMed ID: 28699569
[TBL] [Abstract][Full Text] [Related]
5. A natural language processing framework to analyse the opinions on HPV vaccination reflected in twitter over 10 years (2008 - 2017).
Luo X; Zimet G; Shah S
Hum Vaccin Immunother; 2019; 15(7-8):1496-1504. PubMed ID: 31194609
[TBL] [Abstract][Full Text] [Related]
6. HPV vaccine, Twitter, and gay, bisexual and other men who have sex with men.
Budenz A; Klassen A; Leader A; Fisher K; Yom-Tov E; Massey P
Health Promot Int; 2020 Apr; 35(2):290-300. PubMed ID: 31006017
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Associations Between Exposure to and Expression of Negative Opinions About Human Papillomavirus Vaccines on Social Media: An Observational Study.
Dunn AG; Leask J; Zhou X; Mandl KD; Coiera E
J Med Internet Res; 2015 Jun; 17(6):e144. PubMed ID: 26063290
[TBL] [Abstract][Full Text] [Related]
9. Twitter and brachytherapy: An analysis of "tweets" over six years by patients and health care professionals.
Thomas J; Prabhu AV; Heron DE; Beriwal S
Brachytherapy; 2018; 17(6):1004-1010. PubMed ID: 30131255
[TBL] [Abstract][Full Text] [Related]
10. Assessing the Viability of Social Media for Disseminating Evidence-Based Nutrition Practice Guideline Through Content Analysis of Twitter Messages and Health Professional Interviews: An Observational Study.
Hand RK; Kenne D; Wolfram TM; Abram JK; Fleming M
J Med Internet Res; 2016 Nov; 18(11):e295. PubMed ID: 27847349
[TBL] [Abstract][Full Text] [Related]
11. What are health-related users tweeting? A qualitative content analysis of health-related users and their messages on twitter.
Lee JL; DeCamp M; Dredze M; Chisolm MS; Berger ZD
J Med Internet Res; 2014 Oct; 16(10):e237. PubMed ID: 25591063
[TBL] [Abstract][Full Text] [Related]
12. Comparing human papillomavirus vaccine concerns on Twitter: a cross-sectional study of users in Australia, Canada and the UK.
Shapiro GK; Surian D; Dunn AG; Perry R; Kelaher M
BMJ Open; 2017 Oct; 7(10):e016869. PubMed ID: 28982821
[TBL] [Abstract][Full Text] [Related]
13. Characterizing Twitter Content About HIV Pre-exposure Prophylaxis (PrEP) for Women: Qualitative Content Analysis.
Keddem S; Agha A; Morawej S; Buck A; Cronholm P; Sonalkar S; Kearney M
J Med Internet Res; 2023 May; 25():e43596. PubMed ID: 37166954
[TBL] [Abstract][Full Text] [Related]
14. Using social connection information to improve opinion mining: Identifying negative sentiment about HPV vaccines on Twitter.
Zhou X; Coiera E; Tsafnat G; Arachi D; Ong MS; Dunn AG
Stud Health Technol Inform; 2015; 216():761-5. PubMed ID: 26262154
[TBL] [Abstract][Full Text] [Related]
15. Exploration of Content and Reach of Physical Therapy-Related Discussion on Twitter.
Sabus C; Johns B; Schultz N; Gagnon K
Phys Ther; 2019 Aug; 99(8):1048-1055. PubMed ID: 31329985
[TBL] [Abstract][Full Text] [Related]
16. Facts or stories? How to use social media for cervical cancer prevention: A multi-method study of the effects of sender type and content type on increased message sharing.
Zhang J; Le G; Larochelle D; Pasick R; Sawaya GF; Sarkar U; Centola D
Prev Med; 2019 Sep; 126():105751. PubMed ID: 31226342
[TBL] [Abstract][Full Text] [Related]
17. The Source and Credibility of Colorectal Cancer Information on Twitter.
Park S; Oh HK; Park G; Suh B; Bae WK; Kim JW; Yoon H; Kim DW; Kang SB
Medicine (Baltimore); 2016 Feb; 95(7):e2775. PubMed ID: 26886625
[TBL] [Abstract][Full Text] [Related]
18. Social media analytics and reachability evaluation - #Diabetes.
Karmegam D; Mappillairaju B
Diabetes Metab Syndr; 2022 Jan; 16(1):102359. PubMed ID: 34920205
[TBL] [Abstract][Full Text] [Related]
19. #DoctorsSpeakUp: Lessons learned from a pro-vaccine Twitter event.
Hoffman BL; Colditz JB; Shensa A; Wolynn R; Taneja SB; Felter EM; Wolynn T; Sidani JE
Vaccine; 2021 May; 39(19):2684-2691. PubMed ID: 33863574
[TBL] [Abstract][Full Text] [Related]
20. Utilizing Twitter data for analysis of chemotherapy.
Zhang L; Hall M; Bastola D
Int J Med Inform; 2018 Dec; 120():92-100. PubMed ID: 30409350
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
