Applying Multiple Data Collection Tools to Quantify Human Papillomavirus Vaccine Communication on Twitter

Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States. There are several vaccines that protect against strains of HPV most associated with cervical and other cancers. Thus, HPV vaccination has become an important component of adolescent preventive health c...

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Bibliographic Details
Published in:Journal of medical Internet research 2016-12, Vol.18 (12), p.e318-e318
Main Authors: Massey, Philip M, Leader, Amy, Yom-Tov, Elad, Budenz, Alexandra, Fisher, Kara, Klassen, Ann C
Format: Article
Language:English
Subjects:
Cervical cancer
Classification
Communication
Data collection
Data Collection - methods
Equality
Ethnic groups
Female
Health care industry
Health Communication
Health education
Health information
Human papillomavirus
Humans
Immunization
Interdisciplinary aspects
Interdisciplinary research
Mass media
Minority groups
Original Paper
Papillomavirus Infections - prevention & control
Papillomavirus Vaccines - administration & dosage
Preventive medicine
Prospective Studies
Public Health
Retrospective Studies
ROC Curve
Sexually transmitted diseases
Sexually Transmitted Diseases - prevention & control
Side effects
Social Media
Social networks
Software
STD
United States
Uptake
Uterine Cervical Neoplasms - prevention & control
Vaccination
Vaccines
Words
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Summary:Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States. There are several vaccines that protect against strains of HPV most associated with cervical and other cancers. Thus, HPV vaccination has become an important component of adolescent preventive health care. As media evolves, more information about HPV vaccination is shifting to social media platforms such as Twitter. Health information consumed on social media may be especially influential for segments of society such as younger populations, as well as ethnic and racial minorities. The objectives of our study were to quantify HPV vaccine communication on Twitter, and to develop a novel methodology to improve the collection and analysis of Twitter data. We collected Twitter data using 10 keywords related to HPV vaccination from August 1, 2014 to July 31, 2015. Prospective data collection used the Twitter Search API and retrospective data collection used Twitter Firehose. Using a codebook to characterize tweet sentiment and content, we coded a subsample of tweets by hand to develop classification models to code the entire sample using machine learning procedures. We also documented the words in the 140-character tweet text most associated with each keyword. We used chi-square tests, analysis of variance, and nonparametric equality of medians to test for significant differences in tweet characteristic by sentiment. A total of 193,379 English-language tweets were collected, classified, and analyzed. Associated words varied with each keyword, with more positive and preventive words associated with "HPV vaccine" and more negative words associated with name-brand vaccines. Positive sentiment was the largest type of sentiment in the sample, with 75,393 positive tweets (38.99% of the sample), followed by negative sentiment with 48,940 tweets (25.31% of the sample). Positive and neutral tweets constituted the largest percentage of tweets mentioning prevention or protection (20,425/75,393, 27.09% and 6477/25,110, 25.79%, respectively), compared with only 11.5% of negative tweets (5647/48,940; P
ISSN:1438-8871
1439-4456
1438-8871
DOI:10.2196/jmir.6670