Paper by Steven Gittelman et al in the Journal of Medical Internet Research: “The development of the Internet and the explosion of social media have provided many new opportunities for health surveillance. The use of the Internet for personal health and participatory health research has exploded, largely due to the availability of online resources and health care information technology applications [ – ]. These online developments, plus a demand for more timely, widely available, and cost-effective data, have led to new ways epidemiological data are collected, such as digital disease surveillance and Internet surveys [ – ]. Over the past 2 decades, Internet technology has been used to identify disease outbreaks, track the spread of infectious disease, monitor self-care practices among those with chronic conditions, and to assess, respond, and evaluate natural and artificial disasters at a population level [ , , , , , , , , – ]. Use of these modern communication tools for public health surveillance has proven to be less costly and more timely than traditional population surveillance modes (eg, mail surveys, telephone surveys, and face-to-face household surveys).
The Internet has spawned several sources of big data, such as Facebook , Twitter [ ], Instagram [ ], Tumblr [ ], Google [ ], and Amazon [ ]. These online communication channels and market places provide a wealth of passively collected data that may be mined for purposes of public health, such as sociodemographic characteristics, lifestyle behaviors, and social and cultural constructs. Moreover, researchers have demonstrated that these digital data sources can be used to predict otherwise unavailable information, such as sociodemographic characteristics among anonymous Internet users [ – ]. For example, Goel et al [ ] found no difference by demographic characteristics in the usage of social media and email. However, the frequency with which individuals accessed the Web for news, health care, and research was a predictor of gender, race/ethnicity, and educational attainment, potentially providing useful targeting information based on ethnicity and income [ ]. Integrating these big data sources into the practice of public health surveillance is vital to move the field of epidemiology into the 21st century as called for in the 2012 US “Big Data Research and Development Initiative” [ , ].
Understanding how big data can be used to predict lifestyle behavior and health-related data is a step toward the use of these electronic data sources for epidemiologic needs…(More)”