This chapter will show how text mining can enable us to peer into the relationships between individuals, as opposed to studying moments in time. Reviewing a famous case study that focuses on the French debates in the era of the French Revolution, this chapter reviews the proposal that text mining can discern individuals whose speech was most influential on their generation. The chapter discusses the information theory that lies at the base of the French Revolution study and applies it to a case study on Britain’s parliament. A critical review of the results demonstrates how the careers of Isaac Butt, William Gladstone, and Arthur Balfour took shape against different relationships to past and future. The chapter reviews the algorithm’s abstractions carefully and critically, raising important questions about what each metric shows.