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The Rise of the Novel
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Exercise 8: Narrative form + artistic representation

1 min read

In thinking about topic modeling and metadata for a group of 18th century novels, a particular challenge for me seems to be figuring out a question to explore using these methods which is neither so large that its answer would not be particularly interesting or meaningful nor so small that it is not much different from close reading. So, in trying to both narrow down and expand my interests in genre, form, etc. I really like the idea of combining algorithmic criticism with “middle-distance reading” to find something out about a group of novels that traditional literary criticism — with its dichotomous close and distant reading — can’t really do. I would like to take a group of novels written in the third person OR in free indirect discourse and look at the topics related to or involving artistic representation in the form of writing — so mentions of books, novels, poetry, other kinds of writing — to see if any commonalities pop up and if there might some kind of relationship to be extrapolated or theorized here about narrative form and the presence of narrative artistic representations in the novels.

Exercise8

Research Question!

1 min read

Suppose I give you a book but don’t tell you the title or what kind of book it is supposed to be. Could you figure out the genre just by reading it? Probably; we all have some sense of what makes a fantasy novel different from an autobiography. I am curious if a computer could similarly distinguish different genres of writing - specifically, could one use topic modeling to classify a book? Suppose we develop some algorithm to somehow rate the “genre-similarity” of a huge literary corpus. What genres would we find there? Would they match up with the genres we are familiar with, or would the algorithm group together what we would consider very different novels? I imagine that we would find weird clusters of books, since this is essentially topic modeling but on a larger scale, and the topics we discovered when working with topic modeling were sometimes humanly coherent and sometimes not. But to see the final product of this type of analysis - some big picture of a huge number of literary works, grouped together by some features of language, I think would be pretty cool.

Exercise8

Exercise 8

3 min read

One thing I'd like to use topic modeling and metadata for is to look for a shift from religious communities/dynastic realms and messianic time to nationalism and homogenous time (as described in Anderson's Imagined Communities. To do this, I think it would be best to split a corpus of eighteenth century novels into groups based on their publication date. One suggested grouping is 1700-1750 and 1751-1799, although one could also create more than two groups by making the year ranges smaller (for example, 1700-1733, 1734-1766, 1767-1799). However, it is possible that the later dates may contain a larger number of novels, in which case it might be better to have uneven groupings so that the split of novels between groups is not too disproportionate--though a large time range could obscure when the shift took place. It might be preferable to run this multiple times with different groupings to see how the groupings affect the results.

To identify the shift, I think one thing to look at would be to see whether there are any topics related to imagined communities: that is, any topic where an imagined community (a community where the constituents don't interact with all other constituents) is associated with descriptive words or traits. One particularly useful thing to look for would be the association of country names with other words. Topic modeling could also be used to look for simultaneity in novels, which Anderson argues enables the concept of nationalism and imagined communities. Here it would be helpful to look to see if topic modeling can help identify instances/trends of simultaneity (where characters are acting separately but at the same time). (Topic modeling may not be the best tool for this, but I'm not sure what would be. Perhaps it would be better to look at the frequency of words like "meanwhile".) It would still be interesting to see if words like "meanwhile" show up in topic modeling, and what words they are associated with if they do. Another thing to look for that doesn't require topic modeling is to see how time is described across eighteenth-century novels. Anderson discusses a shift from sacred time to modern time, and this shift could be identified through a rise of the usage of standardized or clock time. Anderson also talks about the newspaper's role in enabling the new sense of time/imagined community, so it might be worth looking at the mention of newspapers (frequency-wise) or seeing if the word "newspaper" appears in the topic modeling at all. If the word "newspaper" does appear in the topic modeling, it would be interesting to see what words the newspaper is associated with.

Exercise8

Topic-Modeling Metadata

2 min read

At first glance, topic modeling doesn’t seem to provide us with a lot of metadata; the outputs that the algorithm generates for us are pretty straightforward strings of words. But I think there’s more to topic modeling than meets the eye, and I would be interested in exploring and analyzing what little metadata topic modeling has to offer us. My research question would be something along the lines of: What can the metadata of topic modeling tell us about topic modeling as a practice, and about the novels they are attempting to topic model?

In order to effectively analyze the metadata of topics, we’d be burdened with the task of creating, or at least documenting, the metadata that’s available for each one. I would begin by tagging each topic with the number of other topics produced alongside it, the number of iterations, the number of printed words, and the presence of stop words or not. I would then create some basic content-related labels surrounding the topics based on what we’ve seen so far, such as “money” or “family” or “hilarious” or “???” depending on the topic. I’d also like to figure out a way to assign the topics a “relevancy score”, or some metric that indicates how much the topic “makes sense” to a human reader or how much meaning we can draw from it.

I think this research question, and its answers, would provide us with a SUPER macro-level picture of what’s going on in a corpus of novels, one worth discussing.

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Exercise 8

1 min read

Research Question: How did the ways in which novels talked about women and social class change from the beginning to the end of the 18th century?

I think that an interesting way to go about answering this question would be to first use metadata, i.e. years of publication, to separate groups of novels written from 1700-1720, 1720-1740, 1740-1760, 1760-1780, and finally, 1780-1800. One could then use a topic modeling tool to create topics for the novels in each of these corpuses, and look for patterns in topics that mention gender or class. Do they tend to focus on beauty and wealth? Or on virtue? Maybe on intelligence and kindness? These questions go alongside the Questions of Virtue that raised by McKeon, and could help to think about how novels answered these questions throughout the century. A further analysis could even look at the titles of the works written during each of the time periods, and a simple word cloud could help to give a sense of what words were common and what words were not.

Tags:

Exercise 8

2 min read

How much do titles foreshadow what the novel is truly about? To what extent do the elaborate descriptive titles of the 18th century novels we’ve looked at reflect the themes with which the novel is occupied? Do the words that appear on the title page reappear throughout, or are they simply there to attract readers?

I’m not entirely sure how to execute this using only the exact topic modeling and metadata tools of the past two assignments, but very similar technology could answer these questions. The topic modeling would need to be limited to a single novel (if we wanted to do this very inefficiently, with tons of iterations), or there would need to be a way to connect the topic modeling to the metadata in such a way that matches novels with themselves. That was poorly explained. What I’m trying to say is that the two technologies would need to be combined in such a way that would allow us to compare words in titles to themes within individual novels. This would allow us to determine—albeit pretty abstractly and inconclusively—how much of a correlation there is between what the title promises the reader and what is delivered.

Alternatively, there could be a cool tool that uses the basis of topic modeling—co-occurrence of words—but examining the titles as well as the body of the text. In novels with “virtue” in the title, what percentage of the words are “virtue” or related terms? And what topic does “virtue” belong to? What does that tell us about novels with “virtue” in the title?

Exercise8

Exercise 8

1 min read

Although the metadata provided us with a lot of quantitative information about the group of novels we studied, there were several aspects of this collection of works that went un-described by the dataset. While completing the exercise, I found myself wondering about the popularity of these novels. Additionally, during the topic modeling exercise, we saw that while some of the topics generated seemed to be random amalgamations of unrelated words, topics that were relatively cohesive and identifiable did appear.

I would like to address the popularity of different topics during the 18th century and combine both metadata and topic modeling to track what subjects people were most interested in reading about. I would first choose several well defined topics (possibilities could include exploration/travel, family, literature/fine arts etc.) and collect data on the individual novels that comprise each topic. Obtaining informationon how many copies of each of these books were printed or sold would most likely require some digging, but if getting a hold of this data were possible, I could then monitor the popularity of each topic over a specified time period.

exercise8

Assignment 8: The Intended Audience

2 min read

Most of our exercises focused on understanding the novels and the literary trends of the 18th century. However, it is also important to understand the 18th century audience that the novels are trying to reach. From the metadata and through topic modeling, it is possible to better understand the intended audience or rather the point of view of the intended audience. Furthermore, as most of the novels we have read were published in 18th century Britain and during the era of the British Empire, it would be interesting to see the places that the novels mention, allowing us a better understanding of the world from the point of view of an 18th century Briton. I would create a map of “TitlePlaces” from the metadata, paying close attention to the locations that were mentioned the most in the metadata. If the novels were focusing on specific locations, it is possible that the audience could easily recognize or relate to those locations, as the authors would want their novels to relate to or influence the audience (e.g. Defoe mentions the “Brazils” and the plantations there to idealize the enslavement of the New World). Afterwards, using the Topic Modeling Tool, I would look for the names of the those locations. I would focus on finding any trends or patterns of words that are associated with popular locations (perhaps England is associated with “civilization” and Paris is associated with “progress”). The purpose of this research is to better understand an average 18 century reader, thereby giving us a better understanding of why authors chose certain techniques, locations, and themes in their novels.

Exercise8

Europe #1?

2 min read

Considering that many of the texts we’ve read were originally published in 18th century England, it would be interesting to revisit Eurocentrism as a potential research topic. These 18th century novels seem to place an emphasis on European exceptionalism, primarily by glorifying European social and ideological customs. Since it might be hard to explore this Eurocentrism with the guidance of single question, I would probably turn to Ian Watt’s idea of formal realism. In the simplest of terms, Watt argues that the novel serves as a reflection of the individual human experience. Contextualizing this with the novels we’ve absorbed this semester, the human experience that Watt identifies seems to be a predominantly European one—specifically pertaining to England.

We discussed this concept briefly in our discussions of Robinson Crusoe, but I imagine it can be further contextualized by using the software from exercises 6 and 7. Using the available metadata, I would create a word cloud for the ‘TitlePlaces’ column and keep an eye out for European locations. I might also experiment with the ‘TitleNames’ and ‘TitleNouns’ categories to see if any results seem specific to Europe (European names, objects, etc.). Additionally, I would run digital facsimiles through the topic modeling software. I would probably use chunks from the novel to this, as that seemed to be the most effective method in exercise 7. After doing this, I’d pinpoint topics that evoke European social conventions, locations, and ideologies. Given the importance of location and setting in this proposed research project, I would also be enticed to input the results of the ‘TitlePlaces’ category into Google My Maps, which is similar to what we accomplished in exercise 2.

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