Objectives To test the feasibility of using Twitter data to assess determinants of consumers' health behavior towards Human papillomavirus (HPV) vaccination informed by the Integrated Behavior Model (IBM). Methods We used three Twitter datasets spanning from 2014 to 2018. We preprocessed and geocoded the tweets, and then built a rule-based model that classified each tweet into either promotional information or consumers' discussions. We applied topic modeling to discover major themes, and subsequently explored the associations between the topics learned from consumers' discussions and the responses of HPV-related questions in the Health Information National Trends Survey (HINTS). Results We collected 2,846,495 tweets and analyzed 335,681 geocoded tweets. Through topic modeling, we identified 122 high-quality topics. The most discussed consumer topic is "cervical cancer screening"; while in promotional tweets, the most popular topic is to increase awareness of "HPV causes cancer". 87 out of the 122 topics are correlated between promotional information and consumers' discussions. Guided by IBM, we examined the alignment between our Twitter findings and the results obtained from HINTS. 35 topics can be mapped to HINTS questions by keywords, 112 topics can be mapped to IBM constructs, and 45 topics have statistically significant correlations with HINTS responses in terms of geographic distributions. Conclusion Not only mining Twitter to assess consumers' health behaviors can obtain results comparable to surveys but can yield additional insights via a theory-driven approach. Limitations exist, nevertheless, these encouraging results impel us to develop innovative ways of leveraging social media in the changing health communication landscape.
翻译:测试使用Twitter数据评估消费者健康行为对人体乳头瘤病毒(HPV)疫苗接种的决定因素的可行性。我们从2014年至2018年使用了三套Twitter数据集。我们预先处理了这些推文并进行了地理编码,然后建立了一个基于规则的模式,将每条推文分类成促销信息或消费者讨论。我们应用了主题模型来发现主要主题,随后探索了从消费者讨论中汲取的关于消费者健康行为对人体乳头瘤病毒(HPV)疫苗接种的决定因素与卫生信息国家趋势调查(HINTS)中与HPV相关问题的答复之间的关联。结果我们收集了2 846 495个推特,分析了335 681个地理编码的推文。我们通过主题建模确定了122个高质量的主题。我们讨论最多的消费者议题是“癌症筛查”;在宣传性推文中,最受欢迎的主题是提高对“HPV致癌症”的认识。 122个专题中,有87个与推广性信息与消费者的准确性讨论有关联性。在IBM的指导下,我们研究了我们的Twitter调查结果与从HINS的对比性理论中得出的结果。在HINS的统计学分布上,可以将这些专题与HIS的统计学流数据流数据流数据流数据流数据流学上进行定位。