Novel Ideas on Religious Toleration During the Age of Enlightenment
David Criscione
What made the Age of Enlightenment? Surely when one imagines the intellectual movement that swept the Western World in the eighteenth century, one thinks of philosophers who promoted ideas of reason, progress, and empirical science. Additionally, we remember how the Age of Enlightenment forged bonds of sensibility and compassion for common humanity across religious and ethnic groups, casting out old tribal affiliations and ushering forth an era of liberty, fraternity, and toleration. Additionally, the Age of Enlightenment coincided with what literature scholar Ian Watt called “The Rise of the Novel.” Literature scholars and cultural historians identify the Age of Enlightenment with the birth of the modern novel with its fictional prose, narrative structure, in-depth character studies, and stirring of romantic feelings. Over the course of the eighteenth century, the commercial print industry churned out books on cheap paper as an ever-expanding and increasingly-caffeinated reading public consumed these novels at a higher rate. Yet what did these novels have to say about Enlightenment ideas? Did novels promote ideas of liberty, toleration, and common humanity, or were they merely an artistic form that coincided with the Age of Enlightenment but really advanced more narrow-minded values? Moreover, which religious communities did the novelists speak favorably, and which did they disdain?
Over the Spring of 2022, I went about figuring out how to test the relationship between novels and religious toleration during the Age of Enlightenment. My solution was to compile popular novels published by Anglophone writers during the Age of Enlightenment and the subsequent Age of Revolutions (1750-1850). With these search parameters, I compiled a total of fifty-six novels, which I downloaded from the free online collection, Project Gutenberg: https://www.gutenberg.org/. The authors of these texts represent the breadth of the eighteenth century Anglophone world, including the British Isles (England, Scotland, Wales, and Ireland) as well as the United States and Canada. Notable writers included Jane Austen, the Bronte Sisters, Charles Dickens, Maria Edgeworth, James Fenimore Cooper, Washington Irving, Henry Wadsworth Longfellow, Edgar Allen Poe, Sir Walter Scott, Percy and Mary Shelley, and even British Prime Minister Benjamin Disraeli. I converted these novels into text files and uploaded and analyzed the files using a Text Data Mining platform designed by Baylor University Data Librarian Joshua Been. The Text Data Mining platform analyzed the novels for words frequently used with searchable keywords (e.g. toleration, Catholic, Protestant, atheist) as well as the sentiment with which authors regarded the keyword (rated high, medium, and low). By having the computer mine the texts, we could identify 1. what novelists wrote regarding religious toleration and religious groups, and also 2. how novelists wrote about religious toleration and differing religious groups. The results of these findings have been posted to a public Power BI dashboard.
In the top right corner of the dashboard, the “Average Sentiment by Contextual Terms” bar graph displays the positive to negative sentiment of searched keywords, with a scale from +1 to -1. At the top with +1 sentiment are words like “believe,” “god,” “freedom,” “Christian,” and “church,” while the only word at the bottom with -1 sentiment was “devil.” Between “god” and the “devil,” we received some surprising results about how authors referred to abstract concepts about religious tolerance and religious beliefs, as well as how they referenced particular religious groups.
Abstract terms like “liberty,” freedom,” “belief,” and “toleration” scored high in positive sentiment, showing the authors’ generally positive regard for those concepts in their novels. As for religious groups, authors wrote of “Jews,” “Indians,” “Protestants,” “Catholics,” and even “idolators” with positive sentiment. However, on the other end of the spectrum, authors wrote about “Quakers,” “Lutherans,” “Catholicism,” “Atheism,” “Hindu,” and “Islam” with low sentiment (from -0.35 to -0.96). So were these seminal novels as open-minded towards religious toleration as we would suppose? Well, it depends. In regards to the abstract concepts, the authors wrote about ideas of religious toleration with positive sentiment. Meanwhile, particular religious groups were written with low sentiment. While this low sentiment may not reflect the views of the authors, these depictions may have negatively influenced the English reading public’s opinions of different faith traditions.
Yet avid novel-readers and English literature scholars alike may hold some reservations of a computer reading novels, nay, mining them, for content. They may ask, “why should a computer read a novel? Isn’t the whole point of a novel that people read novels as they enrich us with characters studies to learn about the human condition?” Perhaps. Yet a human who averages reading a book a week (a reading pace which Pew places in the 90th percentile for American readers) would need thirteen months to read all fifty-six books used in my study. In the meantime, my computer “mined” these books for keywords and sentiment in a couple of hours. Thirteen months versus thirteen hours. You do the math.
However, while my computer’s novel-readings do not enliven its core processor to the nuances of the human condition, its strength lies in processing vast amounts of data in ways human brains cannot. Humans may specialize in close reading and drawing significant themes from written works, but text data mining can identify linguistic trends that occur over a large corpus of data, and visualize these trends in engaging ways. By identifying and visualizing trends, the digital humanities provoke scholars to ask new questions about the data and provoke deeper analysis and broader conclusions. So, computers can read broader and faster than humans, but humans can read closer and deeper than computers. Together, humans and computers can read broader, faster, closer, and deeper than in isolation, uncovering new meanings and interpretations behind texts than before. So, just as mass printing and caffeine reinvigorated the reading scene in the Age of Enlightenment, computers and data analytics are igniting our own reading revolution in the Digital Age.