In the introduction to “Network Theory, Plot Analysis,” Franco Moretti suggests that network analysis can be one way of quantifying and then exploring plot. Since, according to Robert Thompson<\/a>, Charles Schulz’s Peanuts<\/em> “is arguably the longest story ever told by one human being,” network analysis might be an important way for us to understand some aspects of its plot. Put another way, all semester, I’ve been talking about wanting to understand character co-occurrence within Peanuts<\/em>; well, the time has finally come for us to see what we learn about the strip when we consider the frequency of such pairings. <\/p>\n\n\n\n As always, it’s worth saying that what we can see from network analysis is only one small part of the very large story that is Peanuts<\/em>. Nevertheless, it’s worth seeing what this particular lens can teach us.<\/p>\n\n\n\n For this assignment, you will produce one or more network graphs that shows the co-occurrence of Schulz’s characters and begin your analysis of the graph(s). The assignment has one outcome: a You should download Gephi<\/a>, which is open-source software for visualizing and analyzing the properties of networks. Once it’s downloaded, install it on your computer. <\/p>\n\n\n\n I used a couple of<\/a> Python scripts<\/a> to crawl the GoComics data to, first, find the characters that appear in each strip and, second, count those interactions and format those data for Gephi’s use<\/a>. Use git to fetch and pull all the updates to our repository and then find the I will show you how to do these steps. But briefly:<\/p>\n\n\n\n Before you actually click on the “Overview” tab to see the resulting graph, you should take a moment to make a prediction or two. Which characters do you think are going to be the most connected? Which ones do you think will have weaker connections? Why do you think this will be the case?<\/p>\n\n\n\n Jot these thoughts down; they will be helpful later on. <\/p>\n\n\n\n The graph that you will see at this point is randomly distributed. You will want to do a number of things to make it more legible. These include the following, all of which I will show you how to do:<\/p>\n\n\n\n You can also find interesting data to consider in the “Data Laboratory” tab, such as the weight of the different edges between characters. You can also include new data, such as the gender of each character, and then adapt graph in the “Overview” tab to display those genders. <\/p>\n\n\n\n Write about your analysis using Google Docs<\/a>. When you are done, make the Doc public and post a link to it on our blog<\/a>. The post is due by the end of the finals exam period at 5:30 pm on<\/strong> Tuesday, 21 April<\/strong>. Your write-up should contain the following information:<\/p>\n\n\n\n This assignment is worth 75 points. You will be graded on whether your post has all the required items; the quality of the work that you did in trying and evaluating different graphs and their options; and your analysis of the network that you create.<\/p>\n\n\n\n This is a new assignment this semester. That said, I feel a particular debt to Martin Grandjean<\/a>, whose work with Gephi has always inspired me and whose tutorials I look at if I forget how a certain feature works. I also want to thank Sarah Palmer<\/a>, who collaborated with me on my first big network analysis project<\/a>. Finally, my colleague Jeremy Browne<\/a> got all the Peanuts<\/em> data from GoComics in the first place and my other colleague Rob Reynolds<\/a> helped me troubleshoot the Python scripts that I wrote for processing the data. <\/p>\n","protected":false},"excerpt":{"rendered":" Rationale In the introduction to “Network Theory, Plot Analysis,” Franco Moretti suggests that network analysis can be one way of quantifying and then exploring plot. Since, according to Robert Thompson, Charles Schulz’s Peanuts “is arguably the longest story ever told by one human being,” network analysis might be an important way for us to understand […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":34,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_jetpack_hide_featured_image":false,"_jetpack_featured_image_duplicate_dismissed":0,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-398","page","type-page","status-publish","hentry"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/pages\/398","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/comments?post=398"}],"version-history":[{"count":5,"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/pages\/398\/revisions"}],"predecessor-version":[{"id":408,"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/pages\/398\/revisions\/408"}],"up":[{"embeddable":true,"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/pages\/34"}],"wp:attachment":[{"href":"https:\/\/briancroxall.net\/w20dh\/wp-json\/wp\/v2\/media?parent=398"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Nitty Gritty<\/h2>\n\n\n\n
collaboratively authored<\/s> blog post. The blog post is due at the end of our finals exam, Tuesday, 21 April at 5:30 pm.<\/strong><\/p>\n\n\n\nStep One: Download and Install Gephi<\/h3>\n\n\n\n
Step Two: Get the Data <\/h3>\n\n\n\n
char-co-gephi.tsv<\/code> file in the scripts<\/code> folder. <\/p>\n\n\n\nStep Three: Open the Data in Gephi<\/h3>\n\n\n\n
char-co-gephi.tsv<\/code> file from our repository. <\/li>Next ><\/code>.<\/li>Weight<\/code> from “Double” to “Integer.” Click Finish<\/code>.<\/li>Create missing nodes<\/code> is selected and change from New Workspace<\/code> to Append to existing workspace<\/code>. Click OK<\/code>.<\/li>Copy data to other column<\/code>. Select Id<\/code>. Make sure the “Copy to” is set to “Label” and then click Ok<\/code>.<\/li><\/ul>\n\n\n\nStep Four: Ask Yourself What You Expect to See<\/h3>\n\n\n\n
Step Five: Explore the Data in Gephi<\/h3>\n\n\n\n
Step Six: Blog about Your Analysis<\/h3>\n\n\n\n
Grades<\/h2>\n\n\n\n
Credits<\/h2>\n\n\n\n