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Mayer-Schonberger and Kenneth Cukier’s examination of the emergence and power of big data poses, as they argue, questions and problems for the dominance of theory in understanding the world. While I was initially skeptical that big data could provide much insight, they provide compelling examples as to how strong correlations found using expansive and interlinked datasets can reveal new phenomena and disprove causal relationships. However, as a student at a liberal arts university who is not studying computer science or statistics and is immersed in theories proposed by academics; I am interested in how theory and the problematic notion that “the body doesn’t lie” is central to the way that big data is currently used. It appears that many of the examples of big data use are relatively immediate: the onset of the flu, a pregnancy, what someone will buy next. While these questions are interesting for the multinational corporation which seeks to maximize profits every second, they are less useful for those interested in longer periods of time. Such longer periods of time have been tackled in recent years by digital historians using the longue duree approach, who by using massive text archives are able to examine long term trends in ideas, thought, and movements through following terms through time. Such analyses are intensely dependent on theory, not because the relationships are necessarily produced by theory, but rather because the search is informed by theory and the results are typically only interesting or useful to the historian with a theoretical interpretation. I am curious as to how future analytical tools, if developed for history or other ways of understanding longer durations of time, could use this kind of approach to understand the massive amount of data produced through the internet as a hsitorical phenomenon. For example, how might what people search during a flu epidemic change over a period of 20 years (say if a study was done in 2025), and what does that say about changing or static popular conceptions of disease? In what instances do people stop buying from a company due to labor abuses (which tend to be constant throughout a company’s history, whether they be Walmart or Amazon or Apple), and what does that say about forms of resistance to labor exploitation that may be most fruitful?