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Objectives To test the feasibility of using Twitter data to assessdeterminants 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. Wepreprocessed and geocoded the tweets, and then built a rule-based model thatclassified each tweet into either promotional information or consumers'discussions. We applied topic modeling to discover major themes, andsubsequently explored the associations between the topics learned fromconsumers' discussions and the responses of HPV-related questions in the HealthInformation 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 mostdiscussed consumer topic is "cervical cancer screening"; while in promotionaltweets, the most popular topic is to increase awareness of "HPV causes cancer".87 out of the 122 topics are correlated between promotional information andconsumers' discussions. Guided by IBM, we examined the alignment between ourTwitter findings and the results obtained from HINTS. 35 topics can be mappedto HINTS questions by keywords, 112 topics can be mapped to IBM constructs, and45 topics have statistically significant correlations with HINTS responses interms of geographic distributions.  Conclusion Not only mining Twitter to assess consumers' health behaviors canobtain results comparable to surveys but can yield additional insights via atheory-driven approach. Limitations exist, nevertheless, these encouragingresults impel us to develop innovative ways of leveraging social media in thechanging health communication landscape.

Mining Twitter to Assess the Determinants of Health Behavior towards Human Papillomavirus Vaccination in the United States