This is an interesting study of emotion-words in 20th century books, computed from data contained in the Google Books datasets, and using a tool called WordNet Affect, which has developed a taxonomy/ontology of affect-related words and semantic linkages. Something like this tool would be useful for me in my research on shame in nineteenth century texts. The article explains the methodology:
For this study we assessed the emotional valence of the text in books using a text analysis tool, namely WordNet Affect –. WordNet Affect builds on WordNet  by labeling synonymous terms which may represent mood states. Six mood categories, each represented by a different number of terms, have been analyzed: Anger (N = 146), Disgust (N = 30), Fear (N = 92), Joy (N = 224), Sadness (N = 115), and Surprise (N = 41). The text analysis was performed on word stems; the latter were formed using Porter’s Algorithm . Both WordNet Affect and Porter’s Algorithm are considered as standard tools in text mining and have been applied in several relevant tasks , –. We obtained the time series of stemmed word frequencies via Google’s Ngram tool (http://books.google.com/ngrams/datasets) in four distinct data sets: 1-grams English (combining both British and American English), 1-grams English Fiction (containing only fiction books), 1-grams American English, and 1-grams British English.