Maybe we should chat about this:

“Empirical assessment of emotions in literary texts has sometimes relied on human annotation” but now an algorithmic “system determines which of the words exist in our emotion lexicon and calculates ratios such as the number of words associated with an emotion to the total number of emotion words in the text” for novels, Shakespeare, and Brothers Grimm fairy tales (pp. 2, 3). There are no references to Franco Moretti, literary criticism and critical theory, or precedents in fairy-tale analysis such as the ATU Index. Google’s n-gram corpus data and visualization software, which allows you to “Search lots of books” (as opposed to a specific number? are we simply drawing lots? from the “mind of God,” as a Google co-founder once famously called Google), is the Script/ure used (examples of Google data visualizations here).

NRC author Saif Mohammed sees a bright future for the technology in affect surveillance: “Ultimately, he thinks emotion-based software may help us better keep tabs on depression or online harassment and bullying, track emotions on Twitter to forecast riots and better deploy resources, or measure sentiment towards government policies and controversial issues.”