We identified a new taxonomy to describe Twitter use in health research with 6 categories. Many data elements discernible from a user's Twitter profile, especially demographics, have been underreported in the literature and can provide new opportunities to characterize the users whose data are analyzed in these studies. Twitter-based health research is a growing field funded by a diversity of organizations. Public health implications. Future work should develop standardized reporting guidelines for health researchers who use Twitter and policies that address privacy and ethical concerns in social media research.
Background. Researchers have used traditional databases to study public health for decades. Less is known about the use of social media data sources, such as Twitter, for this purpose. Objectives. To systematically review the use of Twitter in health research, define a taxonomy to describe Twitter use, and characterize the current state of Twitter in health research. Search methods. We performed a literature search in PubMed, Embase, Web of Science, Google Scholar, and CINAHL through September 2015. Selection criteria. We searched for peer-reviewed original research studies that primarily used Twitter for health research. Data collection and analysis. Two authors independently screened studies and abstracted data related to the approach to analysis of Twitter data, methodology used to study Twitter, and current state of Twitter research by evaluating time of publication, research topic, discussion of ethical concerns, and study funding source. Main results. Of 1110 unique health-related articles mentioning Twitter, 137 met eligibility criteria. The primary approaches for using Twitter in health research that constitute a new taxonomy were content analysis (56%; n = 77), surveillance (26%; n = 36), engagement (14%; n = 19), recruitment (7%; n = 9), intervention (7%; n = 9), and network analysis (4%; n = 5). These studies collectively analyzed more than 5 billion tweets primarily by using the Twitter application program interface. Of 38 potential data features describing tweets and Twitter users, 23 were reported in fewer than 4% of the articles. The Twitter-based studies in this review focused on a small subset of data elements including content analysis, geotags, and language. Most studies were published recently (33% in 2015). Public health (23%; n = 31) and infectious disease (20%; n = 28) were the research fields most commonly represented in the included studies. Approximately one third of the studies mentioned ethical board approval in their articles. Primary funding sources included federal (63%), university (13%), and foundation (6%). Conclusions. We identified a new taxonomy to describe Twitter use in health research with 6 categories. Many data elements discernible from a user’s Twitter profile, especially demographics, have been underreported in the literature and can provide new opportunities to characterize the users whose data are analyzed in these studies. Twitter-based health research is a growing field funded by a diversity of organizations. Public health implications. Future work should develop standardized reporting guidelines for health researchers who use Twitter and policies that address privacy and ethical concerns in social media research.
Importance Twitter has recently been explored as a data source by researchers in multiple fields, though, as a whole, the research remains nascent. Even less is known about using Twitter to study cardiovascular disease. Objective We sought to characterize the volume and content of tweets related to cardiovascular disease, and the characteristics of Twitter users. Design We used the Twitter Application Programming Interface (API) to access a random sample of tweets from July 2009 to February 2015. We filtered approximately 10 billion tweets for keywords related to cardiovascular disease. We included only English tweets originating from US counties. We characterized each tweet relative to estimated user demographics. A random subset of 2,500 tweets was hand-coded for tweet content and modifiers. Setting Twitter, a social media platform Participants Twitter users tweeting about cardiovascular disease Exposures None Main outcomes and measures Our main outcomes included the volume of tweets about cardiovascular disease on Twitter and the content of these tweets. Results Diabetes (n=239,989) and myocardial infarction (269,907) terms were used more frequently than heart failure (9,414) terms. Users tweeting about cardiovascular disease were more likely to be older than the average Twitter population (mean age= 28.68 vs. 25.36, p<0.01), and less likely to be male (47% vs. 49%, p <0.01). Most tweets (94%) were health related. Common themes included tweets related to risk factors (42%), awareness (23%) and management (23%). Conclusions and relevance Twitter offers promise to characterize public understanding and communication about heart disease.
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