{"id":693,"date":"2017-05-19T10:35:21","date_gmt":"2017-05-19T15:35:21","guid":{"rendered":"https:\/\/researchbdev.wpengine.com\/digital-computational-studies\/?p=693"},"modified":"2017-05-19T14:06:56","modified_gmt":"2017-05-19T19:06:56","slug":"the-novel","status":"publish","type":"post","link":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/digital-computational-studies\/the-novel\/","title":{"rendered":"Graphs – The Novel"},"content":{"rendered":"
\"\"
An automatically generated graph of interactions in the novel. Each time a character speaks, the next speaker is considered to be the recipient. Edges move from the character talking to the recipient. Nodes are sized by out-degree.<\/figcaption><\/figure>\n
\"\"
The same graph, but with the Emma node removed.<\/figcaption><\/figure>\n

Unsurprisingly, Emma lies at the center of the novel, and consequently, its graph.\u00a0 Filtering Emma out of the above graph results in an edge visibility of 36.88 percent.\u00a0 The vast majority of conversations in the novel involve Emma, and this is evident by such a collapse of the graph.\u00a0 However, even without Emma, the other nodes on the graph are still connected to each other.\u00a0 Highbury maintains its structural foundation without her, but the novel inherently takes her point of view.\u00a0 The story cannot exist without Emma, but Highbury can.\u00a0 Franco Moretti performs a similar test in his graphical study of Hamlet, in which he removes Hamlet and Claudius, followed by Hamlet and Horatio.\u00a0 Moretti differentiates, \u201cstability has clearly much to do with centrality, but is not identical to it\u201d (Moretti, 5).\u00a0 Emma is central to the graph, but even with the resulting 36 percent edge visibility, the graph remains stable without her.<\/p>\n

The out-degree of a node indicates the number of edges originating at that node, or in this context, the number of times that character speaks in the novel.\u00a0 Emma has by far the highest out-degree of any node at 360, while the second highest degree is Mr. Knightley at 151.\u00a0 Below that are Frank Churchill with 103, Harriet Smith with 93, and Miss Bates with 83.\u00a0 This ordering makes sense in the context of the novel, as Emma is our protagonist, and Mr. Knightley is her love interest and oldest friend.\u00a0 It may seem surprising that Frank Churchill ranks above Harriet Smith because he only arrives partway through the novel.\u00a0 Though Harriet is Emma\u2019s constant companion, she is also rather quiet, while Frank is more social.\u00a0 Miss Bates appears less frequently than Harriet but has far more to say, explaining her out-degree of 91.<\/p>\n

Consider the difference between this general graph of the novel and a graph of gossip in Highbury.\u00a0 Emma is certainly a prominent figure in Highbury society, but not to this extent.\u00a0 Harriet, too, is far more prominent in this graph than she is as a figure in Highbury.\u00a0 These graphs are, like the novel itself, inherently from Emma\u2019s perspective.\u00a0 They show us gossip in Highbury as Emma sees it, but not in its entirety.\u00a0 This is a significant distinction in evaluating the data of Emma<\/em> as well as understanding the novel.\u00a0 The structure of Emma<\/em>\u2019s plot depends on us reading from Emma\u2019s perspective, and this bias carries over into the data.\u00a0 We only see what Emma sees, and consequently, our model can only show us social interactions as Emma witnesses them.<\/p>\n

\"\"
An automatically generated graph of gossip in the novel. Each edge points from the character talking to the character he or she is talking about. Nodes are sized by out-degree. Characters who speak more often appear as larger nodes.<\/figcaption><\/figure>\n
\"\"
The same graph sized by in-degree. Characters who are more often talked about appear as larger nodes.<\/figcaption><\/figure>\n

In order to generate this graph, every time one character says another character\u2019s name, an edge appears between those two characters.\u00a0 If Miss Bates says the name \u201cJane,\u201d an edge appears from Miss Bates to Jane.\u00a0 This method also takes into account name variations like \u201cMiss Fairfax.\u201d\u00a0 Generating the graph automatically has the disadvantage of ignoring any pronouns, so it certainly misses instances of gossip.\u00a0 In addition, addressing a character in the room then counts as talking \u201cabout\u201d them.<\/p>\n

Note that female characters dominate the graph sized by out-degree, indicating that female voices dominate in Emma<\/em>.\u00a0 However, the genders are more equally sized in the graph sized by in-degree, indicating that both men and women are the subject of gossip.\u00a0 This trend confirms the view of Emma<\/em> as a female-dominated novel, in which female voices take a prominent role.\u00a0 It is also in line with the view of women as gossips, sharing information with one another in order to engage with the community.<\/p>\n","protected":false},"excerpt":{"rendered":"

Unsurprisingly, Emma lies at the center of the novel, and consequently, its graph.\u00a0 Filtering Emma out of the above graph results in an edge visibility of 36.88 percent.\u00a0 The vast majority of conversations in the novel involve Emma, and this is evident by such a collapse of the graph.\u00a0 However, even without Emma, the other […]<\/p>\n","protected":false},"author":105,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[1,25],"tags":[26],"class_list":{"0":"post-693","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-digital-computational-studies","7":"category-jane-austen","8":"tag-jane-austen-project","9":"entry"},"_links":{"self":[{"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/posts\/693","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/users\/105"}],"replies":[{"embeddable":true,"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/comments?post=693"}],"version-history":[{"count":0,"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/posts\/693\/revisions"}],"wp:attachment":[{"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/media?parent=693"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/categories?post=693"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/research.bowdoin.edu\/digital-computational-studies\/wp-json\/wp\/v2\/tags?post=693"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}