Makowski, D., Ben-Shachar, M.S., Patil, I. janeaustenr: Jane Austen's Complete Novels. Hadley Wickham, Romain François, Lionel Henry and Kirill Müller (2021). forcats: Tools for Working with Categorical Variables (Factors). stringr: Simple, Consistent Wrappers for Common String Operations. Journal of Statistical Software, 21(12), 1-20. ggplot2: Elegant Graphics for Data Analysis. textdata: Download and Load Various Text Datasets. R Packages cite_packages() - Emil Hvitfeldt (2020). Other words in a larger font include prominent character names, especially those that appear in multiple novels like “fanny” and “elizabeth”. Some of the more prominent words are “dear”, “lady”, “house”, which, given that Austen writes romances novels in the Regency era were important in the quest to happily married and settled. This word cloud shows the words that more frequently used in Jane Austen novels, while filtering out stop words.

With(wordcloud(word, n, max.words = 120)) The larger the font of the word, the more often it is used. Word clouds are a way to visualize words that are used most often. Pivot_wider(names_from = sentiment, values_from = n, values_fill = 0) %>% bing_austen_sentiments %Ĭount(book, index = linenumber %/% 80, sentiment) %>% sentiment_bing = get_sentiments('bing')Īfter dividing the Austen novels into lines, the sentiment can be calculated by tagging the words that have positive or negative sentiment and keeping a cumulative sum over the span of the line. This lexicon, first published in 2004, contains more than 6700 words that have been tagged with as either positive or negative. In this project, the Bing sentiment lexicon was used. Conducting sentiment analysis on a corpus of work can provide insight into the tone that the author uses.

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