The digital aspect of this project involves creating a visual network of communication using a combination of Gephi and R script.  The goal of this network is to visualize how information moves throughout the community.  I will visualize each character in the novel as an individual node and consider how they interact with one another.  Revealing this network will answer a number of important questions about the text.  Who has and shares knowledge, and who receives it?  How does that knowledge move between people?  Who is the object of the most gossip, and where does the gossip end?  Beyond the value of the model itself, the process of creating it raises a multitude of questions about the text.  We might consider how Austen structures the text around dialogue and narration and when the narrator interrupts sequences of dialogue.  Further, attempting to divide the text into units raises important questions about chapter divisions: Is there only one conversation per chapter? Do conversations ever last multiple chapters?  Why does Austen structure the text in this way, and what can we learn from it?  These are just a few of the questions that digitalizing Austen’s communities can raise.

My networks will track dialogue between characters.  However, digitalizing dialogue proved to be more complicated than it initially appears.  In considering creating a network of dialogue, one might expect to portray the characters as individual nodes with edges connecting them to show interactions.  However, how do we determine where the connection starts and where it ends?  Let us start with a basic example.  Character A is having a conversation with Character B.  We might digitize this with lines moving from A to B and back again for each piece of dialogue.  However, we might complicate this image by adding a third person, C, to the conversation.  When A speaks, is he speaking to B or C, or perhaps both?  How do we determine this?  One way may be to assume that the next person to speak is the one to whom the first character is speaking. Another would be to assume that each character is always speaking to all the characters in the group.  Both these methods pose problems in their accuracy.  Further, let us suppose that A, B, and C are gossiping about a fourth person, D.  How do we portray this connection?  Any automatic method of portraying gossip is inherently flawed, but considering these problems also helps us to consider how dialogue works in the text.

In my research, I discovered a project similar to my own entitled Austen Said: Patterns of Diction in Jane Austen’s Major Novels.  This project explores forms of discourse in Austen’s novels, most prominently free indirect discourse.  The researchers used XML markup to identify each passage in all of Austen’s major works by the speaker and the form of discourse (direct discourse, indirect discourse, or free indirect discourse).  The researchers have helpfully provided their marked up data on their website, and I will use this data in my own study of Austen’s novels.  Although Austen Said primarily focuses on free indirect discourse, their XML markup does provide information about who “says” each passage in the book, which I used in automatically generating my graphs.

I decided to digitally visualize the full novel as well as two individual chapters in greater detail.  I outlined the following steps for creating my graphs:

  1. Automatically generate a graph of gossip in the entire novel in which each character speaks to the next character who speaks, using the XML markup from Austen Said to identify speakers and listeners.
  2. Automatically generate a graph of each of the individual chapters of focus using the same method as in step 1.
  3. Automatically generate a graph of gossip in the entire novel in which each character speaks about any character they name in their dialogue. For example, if Emma mentions Mrs. Weston in her dialogue, I draw an edge from Emma to Mrs. Weston.
  4. Replicate step 3 for each individual chapter of focus.
  5. Manually create the graphs generated in step 2.
  6. Manually create the graphs generated in step 4.
  7. Add gender.

The first step of the project was to perform an initial analysis of the data for the whole novel.  This initial phase identified the speaker of each passage using the “who” attribute of the markup.  The next passage’s “who” attribute became the recipient of each passage.  This step ignores the narrator and characters speaking as each other, and it excludes any additional information, such as gender or social class.  This version of the graph is inherently flawed, as it makes a whole set of assumptions about the text, like the idea that each character is addressing the next character who speaks.  However, it provides a basic starting point from which to proceed.  As this step was almost entirely automated, I performed it first on the novel as a whole, and then on the individual chapters.

In order to accomplish this, my advisor, Professor Crystal Hall, provided me with a piece of code in R that identifies the tagged speaker of each passage and uses the following speaker as the recipient of that passage.  I ran this code using XML markup of the text and uploaded the spreadsheet into Gephi.  Then, I identified the characters I did not want to include in the graph.  These included the narrator, the narrator speaking as a character (indicative of free indirect discourse), and characters speaking as each other.  I wanted to see gossip as it occurs between characters, so though we might consider the narrator as a gossip in this novel, I eliminated her from the graph.  Additionally, I didn’t want “Emma as Knightley” to appear as a separate character in the graph, so deleted these unnecessary nodes.  Then, I rearranged the nodes in order to see them all individually.

The next step was to create a graph that shows characters talking about one another.  Again, Professor Crystal Hall provided me with an R script that searches for a list of character names and creates edges from the character speaking to those they speak about.  This script also accounted for time, considering one chapter as a unit of time.  I then developed the list of character names, making sure to include variations like “Jane,” “Miss Fairfax,” and “Jane Fairfax.”  In Gephi, I then combined nodes that were different names for the same character.  I performed this analysis on both the whole novel and each individual chapter.  I then performed each of the steps above manually for the individual chapters, manually creating my own Excel spreadsheet of my interpretations of the chapters.  Finally, I retroactively added gender as an attribute to all of my graphs so that I could color the nodes accordingly.


Jane Austen’s novels take place in relatively insular country villages. Inevitably, these “three or four families” intermingle frequently and exchange gossip and letters.  In Austen’s novels, information is a vital currency, and its circulation is central to her plots.  Sometimes, information percolates rapidly throughout the community, as it does with Emma’s engagement to Mr. Knightley in Emma.  In other cases, information proves crucial to other characters, as is the case when Elizabeth hides the contents of Mr. Darcy’s letter in Pride and Prejudice.  In this study, I will examine the circulation of gossip in Emma and how information moves within the town.  I will use gephi to model the circulation of gossip in the entire novel, as well as in individual chapters.

To first define our terms, the Oxford English Dictionary defines the verb “gossip” as, “To talk idly, mostly about other people’s affairs; to go about tattling” (“gossip, v.”).  Based on this definition, we might take gossip to mean the discussion of other people’s business.  Further, the OED defines the noun “gossip” as, “A person, mostly a woman, of light and trifling character, esp. one who delights in idle talk; a newsmonger, a tattler” (“gossip, n.”).  Using these two definitions, we might develop a more complete understanding of gossip.  Generally, we will take gossip to mean the act of sharing information about other people, but the term is loaded with connotations.  Firstly, although both men and women in Emma participate in gossip, it carries a feminine connotation, and we will further explore that later.  Additionally, we might expect that those participating in gossip have no personal investment in the object of gossip.  The news they are sharing is, by all accounts, none of their business, but, presumably because they are idle women, they have nothing else to engage them.[1]  The term “gossip,” then, carries with it highly gendered and patriarchal implications, even when applied to a variety of contexts.

Other scholars have already written extensively about gossip in Jane Austen’s works, and a few specific articles are foundational to my work.  In their article “The Tittle-Tattle of Highbury,” Casey Finch and Peter Bowen discuss the societal power of gossip in Emma and the alignment between public and private.  Gossip makes private affairs public and is “the very ground upon which the community is articulated, identified, and controlled,” (Finch, 2).  Also foundational to my work is the notion of gossip’s inherent femininity; it carries connotations of female idleness and triviality.  Scholars before me have argued that Austen uses gossip in a way that provides women with a degree of power and subverts preconceived notions of gossip as inherently useless.  In the article “Homespun Gossip: Jane West, Jane Austen, and the Task of Literary Criticism,” Erin Goss argues exactly that, and goes so far as to say that “one of the myriad of tasks that Austen sets for herself is the redemption of gossip, as so often in her novels, the reader – along with the characters – must come to accept and even condone gossip that is initially seen as suspect,” (Goss, 170).  Finally, scholars have drawn connections between gossip and Austen’s use of free indirect discourse, which I originally intended to explore in this project.  Finch and Bowen make this claim in their work, and “Jane Austen and the Impact of Form” by Frances Ferguson provides another foundational work for my understanding and critical analysis of free indirect discourse.

Gossip is generally considered a feminine pastime, bringing to mind vapid or silly women with nothing else to do but gossip about their neighbors.  However, Austen legitimizes gossip in her narrative, as it provides information to the characters and to the reader.  In her article “Homespun Gossip: Jane West, Jane Austen, and the Task of Literary Criticism,” Erin M. Goss locates the history of marginalization of the female gossip in the etymology of the word “gossip.”  The definitions of the word develop from a godparent, to a woman’s closest friends, to the modern definition of a woman who shares idle news.  Through these changing definitions, we see that the gossip has shifted from a vitally important member of a family’s circle to an insignificant, gossiping woman.  Goss writes, “Gossip then carries within itself the history of its own marginalization; once the name of an official and even sacramental addition to a family structure, it comes to be the marker of a denigrated and specifically feminine form of discourse that is, at best, useless,” (Goss, 167).

Although most if not all of the characters in Emma participate in gossip to some degree, we might consider Miss Bates the town gossip, and even the voice of gossip[2].  She is in many ways the negative stereotype of the gossip; she is a busybody, constantly prattling on about one insignificant thing or another.  However, we learn to empathize with Miss Bates, as does Emma.  Despite her sometimes annoying tendencies, Miss Bates is a devoted and kind friend and entirely harmless.  Further, as a relatively poor, unmarried woman, she finds herself in need of other characters’ company and empathy, as Mr. Knightley points out to Emma.[3]  In terms of causing harm to the other characters, Emma is far more to blame than Miss Bates.  Gossip “serves as a genuinely alternative mode of communication for women who have been historically excluded from dominant discourses; in one and the same movement, gossip is dismissed as feminine ‘tittle-tattle’ and put to use as a serious and privileged form of knowledge,” (Finch, 3).

Frank Churchill is a central figure in Highbury, but until the second volume of the novel, we only hear about him from other characters.[4]  He is continually absent, but his absence endears him to the residents of Highbury and ensures that a “lively curiosity prevails” in the town regarding his life (Emma, 14).  As the child of Mr. Weston, Frank Churchill holds a position of significance in the town and is often paired with Emma Woodhouse as a potential match.  The fact that Mr. Churchill has visited his father, even for his wedding to Miss Taylor, is indicative of his unreliability.  However, we as readers gladly overlook this fact in the face of the town’s active interest in his life.  He is thought to be wealthy, charming, and single, all traits that appear to be true when he arrives in the town.  Austen spends the entirety of the first volume building up Mr. Churchill’s character, so by the time he actually arrives, we (and Emma) have no choice but to view him as an attractive and eligible bachelor.  Of course, the implications of this impression are that when his engagement to Jane comes as a shock to Emma, we too are just as surprised.  In this way, Austen shapes our perceptions of a character through gossip before we actually meet him.

Just as notable as whose voices are the loudest is whose are silent.  Doctor Perry is a significant character in that other characters frequently refer to him, but he never actually appears.[5]  The residents of Highbury love to look to Doctor Perry for medical advice, and he seems to be an expert at telling them what they want to hear.  Mr. Woodhouse is the character to most frequently cite his advice.  In one notable scene, Doctor Perry reluctantly acknowledges “that wedding-cake might certainly disagree with many – perhaps with most people, unless taken moderately,” (Emma, 16).  However, a “strange rumour” later circulates about the Perry children eating cake, indicating that Doctor Perry has only told Mr. Woodhouse what he wants to hear.  In this way, he encourages Mr. Woodhouse’s fears, and he likewise confirms the preconceived notions of other characters in the book.  This is one of the only instances in which we receive Doctor Perry’s exact language, but of course we only hear from him through free indirect discourse.  The statement that cake can be unhealthy “unless taken moderately,” reveals that Doctor Perry is both pandering to what Mr. Woodhouse wants to hear while still giving medically sound advice.  This instance of free indirect discourse is the closest we get to Doctor Perry, as he does not directly appear anywhere in the novel.  Instead, we hear his medical advice from the residents of Highbury and, as seen above, occasionally through free indirect discourse.  Doctor Perry serves as a reflection of the thoughts and desires of the other characters without having a concrete presence in the book.

In this project, I will explore gossip in Emma through a digital lens.  These ideas will be fundamental to my work as I attempt to digitally examine the way information flows throughout Highbury.  I will focus first on the full novel, then on two specific chapters.  For more information about those chapters, please see this post.

[1] In constructing this definition, we already begin to see how Austen deconstructs the notion of gossip, namely regarding the idea that it is unimportant.  Even if two gossiping characters have no apparent relation to the object of their conversation, the social goings-on of Highbury are of great import to the woman of the story due to their reliance on marriage for a suitable future.

[2] Miss Bates’s role as the town gossip allows her to hold a good deal of information, and she contributes significantly to the network of communication we see in the book. In digitalizing this network (as discussed in the Methodology section), we might expect to find her at the center of the network, one of the most frequent contributors.  However, it also seems likely that she is one of the least gossiped about, as her social standing ensures that she is not a key player in Emma’s romantic endeavors outside of her ability to share news.

[3] “She is poor; she has sunk from the comforts she was born into; and, if she live to old age, must probably sink more. Her situation should secure your compassion,” (Emma, 295).

[4] In considering a network of gossip, we might expect to find that Mr. Churchill is a significant figure in terms of gossip about him, but his participation is a different story, at least in the first volume.  Until the second volume, Mr. Churchill only engages in the network through a few letters, and after that he becomes a much more vocal participant.

[5] As we never hear from Doctor Perry directly, we might expect to see him in the network as one gossiped about but not engaging directly in the network himself.

About the Chapters

In Volume 2, Chapter 3 of Emma, we learn that Mr. Elton is engaged.  This chapter is useful in a study of gossip for several reasons.  The chapter begins with a conversation between Emma, Mr. Woodhouse, and Mr. Knightley.  The three discuss a recent party, but Emma and Mr. Knightley are mostly having their own conversation while Mr. Woodhouse interjects with only tangentially relevant comments.  Just as Mr. Knightley is telling Emma that he has some interesting news for her, Miss Bates rushes in and announces that Mr. Elton is engaged.  This news has arrived through a letter to the Coles; Mr. Cole shared it with Mr. Knightley while Mrs. Cole shared it with Miss Bates.  The path of gossip from Mr. Elton to the Coles and now throughout Highbury is significant in the study of this graph.  It is also notable that the information comes from outside and enters the town, where is percolates.  Additionally, we see characters react to the news and discuss it in a group.  This chapter, then, is rich in considering the flow of gossip.

Volume 2, Chapter 8 depicts a party at which we learn that Jane Fairfax has received a mysterious gift of a pianoforte.  We see news of the gift travel throughout the party, and we hear the gossip from several different characters.  This chapter reads almost like a mystery story as characters try to discern who the unseen donor could be.  It is an excellent example of gossip in Emma, as we see how the residents of Highbury gossip with one another.  The party becomes a microcosm of the town; likely all the major characters are there, and we witness how ideas circulate among people.  We hear from two notable characters about their opinions. Mrs. Weston, who often reflects Emma’s own matchmaking tendencies, suggests that the gift-giver could be Mr. Knightley, while Frank Churchill, the donor himself, allows Emma to take the lead in her theorizing.  This chapter allows us to see how gossip circulates in the community and is an ideal sample for study.

Liberal Arts and Technology: Charlotte Carnevale Willner (’06) and Dave Willner (’06) at Bowdoin Breakfast

Bowdoin alumni Dave Willner (’06) and Charlotte Carnevale Willner (’06).

The Spring 2017 Bowdoin Breakfast guests are Charlotte Carnevale Willner (’06) and Dave Willner (’06). Charlotte and Dave work, respectively, at Pinterest (Safety Manager) and Airbnb (Head of Community Policy) in the San Francisco Bay area. Having majored in Humanities (Art History and Anthropology/Arctic Studies), they both started fresh out of Bowdoin at Facebook, in the areas of conflict resolution and safety services. As young people in emerging fields at Facebook, they were in charge of making decisions about data and content during incredible times, and attribute their liberal arts education to helping them with the problem solving they faced.

DCS is excited to host the Willners in DCS 1200 on March 27 and DCS 2017 on March 28. In addition, we invite students and colleagues to join us in the VAC 3rd Floor Common Area at 4:00 on March 27 for an informal conversation about the role of the Liberal Arts in Silicon Valley. Light refreshments will be served.

The Coding Literate Journalist

At the core, coding is an effective method in conveying information. A journalist, in particular, can tell more engaging stories by understanding the ways in which information is collected and displayed with code. They don’t necessarily need to be programming gurus, however a baseline understanding on the possibilities of Computer Programming can help journalists effectively communicate what a particular software project does.

Alex Richards designed the course Coding for Journalists “for people who have some grounding in data journalism already and experience with spreadsheets and database managers. Helpful to understand Excel functions, for example, some basic SQL.” The course is now available as a set of self-guided tutorials with sample code and data at Richards’ site:

Here you can learn how to use Python, a programming language, to scrape data from the web, parse records that fall across multiple lines, make a reusable function, geocode, work with APIs and databases, unlock data stuck in a database, practice data cleaning, and more! However, this isn’t the only place to learn programming. The Internet is scattered with a plethora of coding tutorials, some of which are:,,, and

‘Eurydice’ Play Incorporating Digital Design

Eurydice logo courtesy of South Coast Repertory.

On March 2, 2017 at 7:30 pm to 9:00 pm in Memorial Hall, Wish Theater, the Bowdoin Theater and Dance will open Eurydice, a contemporary, theatrical event that explores the power of love, loss and memory.

In this Greek myth Eurydice leaves her wedding with Orpheus for the underworld, searching for her father – but the reunion is costly. Trapped on the opposite side of death, Orpheus fights to retrieve his bride, making a deal that seals both their fates.

The incorporation of digital design began with determining what the play Eurydice needed to be projected, for example, an animated raining elevator. With subjects and scenes determined they were able to use Autodesk Maya, 3D computer graphics software, to incrementally build models needed for the play.

AutoDesk Maya Editing Environment

Professor Ryan MacDonald noted that “the most time consuming animations were the water simulations: River, Ocean, Rain, etc.” He built these animations using a plugin called Bifrost within Maya. From that point the works were put into After Effects, post- production application used for film- making, for fine tuning and exporting. Finally, Isadora, a graphic programming environment, was used to build a hierarchy between videos, which can be juxtaposed, moved specifically on the stage, and timed to the scenes.

Tickets are free. Advanced tickets can be reserved starting February 9, 2017 at Smith Union (207-725-3375) or at the door on the night of the performance. Limited Seating.

More DH Training Opportunities

For colleagues interested in the Mellon Summer Fellowships or using FDC support for training related to Digital Humanities, here are a few more resources to keep in mind:

  • Digital Humanities at Oxford (DHOxSS), July 3-7 with tracks related to machine learning for text analysis, digital musicology, and social humanities at a global scale:
  • Humanities Intensive Learning and Teaching Institute (HILT) 2017, June 5-9, UT Austin with tracks on Scalar, starting a DH project, Python for text analysis, and using DH as a critical and collaborative method (special focus on Black Publics):
  • Re-Boot Camp 2017, June 12-16, McGill University, a week-long course “Introduction to literary text mining using R”:
  • list of bootcamps and workshops curated by the Price Lab at UPenn


Geographic Mapping of Google Suggestions

Zeitgeist Borders is a search engine that allows for users to distinguish what others are looking for on Google at a given point in time and cultural contexts.

Excerpt of UN Women advertisement campaign against gender-based discrimination toward women. Since this campaign controversial suggestions are regularly banned by Google, replaced by non- offensive ones, or turned off.

Google’s autocomplete technologies serve to make the human- computer interaction more efficient by attempting to predict the word or sentence a user may input after only a few characters have been typed into a text input field.

Antoine Mazièrez states that “[w]hile past searches, account preferences and browsing interests differ for every individual logged user, location- specific suggestions is the only universal discriminant for suggestions, whether the user is logged in or not. Several measures allowed us to establish which elements are used by Google to perform such content discrimination: the public IP that originated the request and the “hl” (which stands or Human Language) parameter passed along with the query that express which language the user is commonly using.”

Here, the user entered “Why my dog.” On the left there are common suggestions. When you mouse over one of the suggestions it will highlight the countries with different shades to indicate the ranking of the given suggestion for the given country.

If you’d like to test it out Antoine Mazièrez’s project for yourself explore this link:


Mazieres, A. (2016). Georgraphical projection of Google's suggestions diversity. In 3rd GESIS Computational Social Science Winter Symposium.

Digital Data to Perserve and Recreate Lost Art

Factum Arte, based in Madrid, London, and Milan, consists of a team of artists, technicians, and conservators dedicated to digital preservation and recreation of lost art.

3D scanning of Paolina Borghese using NUB 3D SIDIO Scanner, Galleria Borghese, Rome, April 2013

Factum Arte’s approach to technology includes buying what they need for specific tasks and designing and fabricating the needed technology when it doesn’t exist. They write software and design operating systems to handle information. They currently use 3D scanning for cultural heritage conservation, photogrammetry, casting, recordings in two and three dimensions, multilayered files and conservation, and new technologies in print making.

Factum Arte’s successful innovations have had a strong influence on conservation methods and are redefining the role facsimiles play in the protection of cultural heritage. The Digital Information that is recorded has been used for documentation, monitoring and the production of 2D and 3D facsimiles which retain the surface complexity and characteristics of the original.

Interested in learning more? Explore their website at

“Visual Effects in Film – Art, Craft, and (Sometimes) Bad Movies”

On Friday, February 17th in Kresge Auditorium at 12:30- 1:30 pm, Dave Fogler, a Bowdoin alumnus of 1990, will be accompanied by the Industrial Light + Magic in 1997 as a miniature model maker on Starship Troopers. During his eight years in ILM’s traditional model shop, Dave contributed to eight motion pictures including Star Wars: Episodes I and IIGalaxy QuestArtificial Intelligence: AI, and Pearl Harbor. In 2005, Dave transitioned to digital modeling and texturing for Star Wars: Episode III and has gone on to supervise the work on all five Transformers films, Indiana Jones and the Kingdom of the Crystal SkullAvatarPacific Rim, and Star Wars: The Force Awakens. Currently, Fogler is the Associate Visual Effects Supervisor on Transformers: The Last Knight.

A Maine native, Fogler has a B.A. from Bowdoin College and a Masters of Fine Arts from The University of California at Berkeley.

Logistics: Friday, February 17th in Kresge Auditorium, Visual Arts Center at 12:30- 1:30 pm.