The introduction opens with the work of researchers such as biologist Peter Turchin, who argues that he can distill the massive volume of textual data on human society, easily reduce human culture to variables, and create not only descriptive models of the human past, but also a predictive machine. It contrasts predictive fantasies with the “hybrid” studies where historians and mathematicians have joined forces to apply text mining – the literal count of words from the past – as a tool for modeling how cultures changed in the past. Reviewing recent work from historians and other specialists in text mining, it sets forth the broad aims of this book – to map out how researchers can take a digital, quantitative approach to illuminating history that eschews naïve interpretation, and instead provides a robustly accurate, original, and profound dimension to this complex discipline.