rcdh

My Semester Made Visible

/ Jana Rosinski / Leave a comment

Last week in RCDH, Collin challenged us to visualize our semester. He left the form and content up to us. As I tend to do, I thought it would be interesting to look at it from the level of composites, allowing me to focus on different intensities through different lenses of focus.

From Tim Baker and Chris Shier’s gifmelter, I started with a gif that became an inside joke between Jason, Lindsey and myself after I used it as a response in a course last semester. Breaking the constraints of the gif (rectangle, perception based on timed loops), the image can be viewed differently. I think this particular iteration takes on new meaning at this scale (particularly poignant in its ability to be broken apart and pretty representative of this semester):

meltgif.jpg

 

A significant event for me this semester was presenting (for the first time) at 4Cs. The panel I presented on was well received, but it also projected. These are ideas that are very much unsettled, active. Threads from this text network have been pulled, followed, and have connected me to other people/texts/ideas.

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Another significant event this semester was participating in THATCamp CNY. While I didn’t showcase/workshop anything, I was party to interesting tools, conversations, fruit trays, and distributed dh connections across the campus. I wanted to do something with my tweets to reconstruct the events of those two days, as well as account for the retweets and favorites that connected each of my own tweets, as well as tweets I was drawn to saving/responding to. This is rather messy, but it’s an attempt at a sort of network (this is only the first of two days and chronicles the movement of my tweets + tweets I was mentioned in):

 

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Key:

  • solid orange line: quoting speaker at THATCamp
  • solid black line: RT from someone in attendance
  • solid green: response to someone in attendance
  • solid purple: mentioned by someone in attendance (but not present)
  • dotted blue: favorited by someone not in attendance
  • long dashed black: favorited and RT by someone in attendance
  • dotted black: favorited by someone in attendance
  • black names: people present
  • blue names: people distant

Out of 17 tweets from those two days, 12 were tweets I RT or favorited. It’s debatable how to measure the furthest reaching; the picture of @ahhitt and I with Otto the Orange had the most favorites and left the central NY area, but the response/comment I made to @ahhitt that evoked @s2ceball might be the furthest reaching, if she is still in Oslo on her Fulbright…

Not pictured: Instagram foods and activities and other odd things; readings; notebooks and doodles; calendar of work and due dates; schedule of sleeping/waking; the starts and stops of an exercise routine; how many/little miles I walked each day; the amount of muscle rub applied to my “computer neck” on a daily basis; how many times I responded “[sigh] goooooood” when asked how I was doing vs. some other response.

Macroanalysis

/ Jana Rosinski / Leave a comment

This week in RCDH, we are discussing Matthew L. Jockers’ Macroanalysis. My role is that of catalyst, so I will work to synthesize the posts of my peers.

Jason appreciated having to read methodology more closely, explaining that in (humanities?) scholarship, method is usually not as developed or attention getting as arguments and conclusions being put forth. He also remarked that he respected Jockers’ balanced approach to making a case for more distant reading methods without diminishing more commonly used close methods; Jason explains “he’s advocating for scholars to use all of the available tools at their disposal”. Jason also found himself thinking about what rhetoric can bring to DH instead of the other way around, which he admits is how he has been thinking about our readings: DH makes him think of tools in these methods, while rhetoric makes him aware of the choices that go into creating, using, and analyzing these tools and their use. Jason ends by raising questions about difference in what can be gained distant reading a corpus of texts vs. a text, ultimately wondering what disservice we do to ourselves by seeing them as situated in different camps, caring for different matters.

Romeo appreciates Jockers’ readability and balanced concern for close and distant methods, which he highlights through Jockers’ definition of macroanalysis—that moving between micro and macro scales is most effective as these approaches inform each other. Romeo finds Jockers’ rationale for macroanalysis compelling, explaining that “He argues that macroanalysis is just another means for evidence gathering and that to embrace new approaches and methodologies to give way to new possibilities of analysis.” With attention to size of information/texts one is working with, Romeo condenses Jockers’ succinctly in describing how a macroanalytic (and computer assisted) approach can reveal information a researcher would otherwise miss (beyond unassisted human ability).

Lindsey, like Romeo and Jason, appreciated how accessible and interesting Jockers’ writing about DH methods is, even seeing it as a text not just about macroanalysis, but caring for DH methods more broadly. She was struck by thinking about research methods, more specifically, she realized she has been approaching reading our DH texts from a composition frame of reference, which surprises her because she is more trained in rhetoric. She is know wondering how DH might intersect with her interests in visual analyses of bodies, performances, and sexuality and what she might take from our course conversations “to conceive of a project that conducts a macro analysis of the rhetoric of our visual culture”. What she is now thinking about is what DH tools and methods there might be to study the visual—”how can a macro analysis account for the rhetorical study cultural artifacts?” Are DH methods limited to alphanumeric texts?

Despite the different points of engagement with Jockers’ texts, it seems like my peers are engaging with methodology/methods more deeply, moving from reading to understand how they are done to wondering what they might do with them in their different areas of interest in rhetoric and composition—perhaps a move too from wondering what is possible/potential to imagining what is possible/potential as DH work.

and how

/ Jana Rosinski / Leave a comment

In attempting to grasp topic modeling, I found it helpful to cluster together the readings from Andrew Goldstone and Ted Underwood, Meghan R. Brett’s introduction to topic modeling, and reviews/responses from Andrew Perrin and Laura Nelson to the Poetics special issue on topic modeling. My understanding of topic modeling is that within a large corpus of texts (huge, like 1000+), TM tools mine the texts by grouping words across the corpus into topics, or patterns of co-occurring words (a relationship of similarity). These topics are then examined by the researcher (who must know something about this text corpus to be able to understand the topics found) and illustrated as a befitting visualization that makes visible these topic relationships.

As I was reading, I noticed my questions seemed to echo questions I have had since I started reading about distant reading, text mining, and visualization a year ago. While I think my technical understanding of these methods is becoming more robust through engagement with work using such methods (and showing how they used the methods), the how is still obscure to me. I pulled quotes from these pieces (that are in ways at odd with one another in how they see TM as useful) that are helping me with the how:

Goldstone and Underwood: “The strictly linguistic character of this technique is a limitation as well as a strength: it’s not designed to reveal motivation or conflict” + “This technique can reveal shifts of emphasis that are more gradual and less conscious than the ones we tend to celebrate.”

TM, as advocated by Goldstone and Underwood, is rigorous enough that it should be considered evidence (product of research) to make claims/questions within a discipline. Their account acknowledges the limitations of this method in that it loses meta information within a text (does context still work at this scope? in these methods?), but affirms the method as a different way of seeing how knowledge has emerged within a discipline/disciplinary set of texts. The how might not have otherwise been visible.

Brett: “Topic modeling is not necessarily useful as evidence but it makes an excellent tool for discovery.”

Brett views TM as a part of research—making patterns visible to then pursue. I think this view of how TM is used, in comparison to that of Goldstone and Underwood, is a divide that emerges in differing scopes of text analysis. How this is determined, I am still uncertain other than varying engagements with the methods; but, what I do notice is how discovery through these methods is differently valued.

Perrin: “But culture is not just language, language is not just text, and text is not just words. Since these methods actually analyze text (not language and not culture) we need to attend to the processes by which culture becomes language and language becomes text.”

Perrin critiques TM because it cannot account for the context of texts—texts (as a collection of words) read through these methods cannot make certain relationships visible. This doesn’t appear to be the argument that I once thought existed between the values/constraints/affordances of “close” and “distant” reading (time with one text read closely v. time with a group of texts read for patterns—we have read much that complicates this) but an assertion that while these methods may make certain patterns visible, they cannot make others. Or, they might give the illusion of patterns that are distorted. Other than making this disclaimer in a methods section, I wonder how else we might account for contexts—especially in large corpora.

Nelson: [topic modeling] “It definitely will not magically help us understand the black box of culture. It’s science, not magic, and any science takes work.”

Nelson, who takes Perrin to task in arguing that understanding texts is a way to help us understand society (the context that Perrin argues is lost in texts that TM methods read). Nelson outlines what TM can and cannot do, making the usual disclaimers about understanding available options, methods as best fit for questions/data, and assumptions behind each method. What struck me in Nelson’s account (it should be noted that this is from sociology) was describing how these methods are science.

And How: I’m left wondering about how we see relations/patterns and meaning; this sounds simple, but what relations have our attention make for great variances in meaning. And while I think this is the point—the affordances and constraints of the methods—how are they (texts to topics, topics to relationships, relationships to patterns, patterns to visualizations, visualizations to relationships, relationships to meaning) considered?

microscopic, not myopic

/ Jana Rosinski / Leave a comment

This week’s readings on “microscopy” were absolutely captivating, providing an opportunity to engage with “scale”. My understanding of scale prior to these readings was more akin to an awareness of its existence and influence to generically understood (based on my limited knowledge) matters of concern such as: size of data set, how closely/distantly a text is being looked at, what can be made visible in terms of patterning, and different tools fitted to size/task of the data set.

I collected scraps from three readings that engaged with scale in interesting ways (note: I might be discussing scale lacking some nuance…): interface/language with range and “tuning-in-ability”.

Matthew Jockers and Julia Flanders “A Matter of Scale”: “We’ve tried to create an interface that supports that kind of shuttling between different levels of scale: seeing patterns, seeing outliers, zooming in and zooming out. The tools aren’t very good yet, but they’re getting better” (17).

Jockers and Flanders work to dissolve the binary between micro/macro data sets that typically get associated with distinct rendering/reading processes and products. In advocating for more discursive markup languages, this seems to be a call for tools that will allow for simultaneously micro/macro analysis to keep both in sight.

“I think you and I must begin from this point of agreement and now work our way towards what the photographers call depth of field. How do we alter the f-stop and shutter speed so as to keep as much in focus as we can?” (17).

This imagining was absolutely engrossing and reminded me of the concept of mise-en-scene—as everything within the shot, from composition, to sets, to props, to actors, to costumes, to lighting—is taken in through the scene. If we had the ability to tune in to these different elements and their connections to the composition of the text, what might we see?

Elizabeth Losh’s “Nowcasting/Futurecasting: Big Data, Prognostication, and the Rhetorics of Scale”: “Because of the distance at which such large collections of cultural objects become legible, we are reduced to being passive spectators as the map grows progressively larger than the territory” (450).

Losh brought to mind questions of when (timing) we can engage with cultural objects, particularly those that are born digital. Traditionally, DH work has directed its attention to print text collections (that are thus past), but there is (was?) a push (by who/what?) toward using DH methods to study emerging (not yet) culture. I wondered, in reading this, if futurecasting was essentially establishing patterns/trends that are in the process of happening based on what has happened?

“Rather than aspire to a predictive humanities, the task of “nowcasting” rather than “futurecasting” may promise a methodology of more engaged research in which the cultural, political, literary, artistic, and material life of the present becomes the focus of attention” (447).

In terms of time, I am having trouble understanding the difference between “future” and “now”, perhaps based on how I am imagining “future” (I wonder what implications this has). It seems that both would be attending, or tuning-in, to happening culture more closely, instead of waiting for it to pass to collect and examine.

Geoffrey Rockwell’s “What is Text Analysis, Really?”: “Rather than developing tools based on principles of unity and coherence we should rethink our tools on a principle of research as disciplined play” (212).

Rockwell is complicating the scale of the text we engage with by working to reterm “concordance” as a hybrid text—instead of looking to establish unity across a text by looking for patterns of coherence, a hybrid tunes into a text that is created by the original text and user choice—a text that is not original (of the author) nor of the concordance provoker. This shifts the scale of text that is being engaged, allowing for different “play”, or methods of interaction.

Rockwell proposes a portal model for text analysis tools that “makes available a variety of server-based tools properly supported, documented, and adapted for use in the study of electronic texts”, a “virtual library” (215).

These are only a part of a much more complex and interesting picture imagining of scale, but I appreciate the ability to trouble the macro/micro binary (myopic vs. panoramic) as something more akin to focus stacking: the combination of multiple images taken at different focus distances to create a resulting image with a greater depth of field than any of the individual source images (from Wikipedia).

"Top left are the three source image slices at three focal depths. Top right are the contributions of each focal slice to the final "focus stacked" image (black is no contribution, white is full contribution). Bottom is the resulting focus stacked image with an extended depth of field." - from Wikipedia "focus stacking"

“Top left are the three source image slices at three focal depths. Top right are the contributions of each focal slice to the final “focus stacked” image (black is no contribution, white is full contribution). Bottom is the resulting focus stacked image with an extended depth of field.” – from Wikipedia “focus stacking”

If microscopy aims to view objects that cannot be seen with an unaided eye, having techniques for “disciplined play” (Rockwell) at varying scales allows for different, and perhaps simultaneous, focus; allowing for close looking that is far from myopic.

metadata mediation

/ Jana Rosinski / 1 Comment

In RCDH this week we’re discussing metadata by way of a collection of interesting readings. Jessica Reyman’s “User Data on the Social Web: Authorship, Agency, and Appropriation” (and texts she has shared via Twitter @jessreyman) primarily occupied my interest. I feel like I know enough about metadata to nod along in conversations where it surfaces, to understand that what it can index about data created on the web is tremendous (see the cross space ads encountered that track patterns of search and purchase or these Twitter metadata visualizations), that it is aggregated by large (unseen or hiding in plain sight) entities, and that the line between it and what I “create” on the web is grey. Reyman gets at this grey area by exploring the complexities of using social web technologies, recognizing all of the productive activities that occur—not only the creation of content, but the overlooked generation of data (515). Reyman poses the following:

  • How do we write on the social Web?
  • How do we write ourselves through the social Web?
  • And how do we write the social Web? (516)

It is Reyman’s argument that data is not merely the by-product of algorithms and aggregation formulas, but “a dynamic, discursive narrative about the paths we have taken as users, the technologies we have used, how we have composed in such spaces, and with whom we have participated” (516). Reyman provides examples of different social web platforms policy language on the distinction (or not so clearly delineated) between data the sites collect (which is framed through a rhetoric of enhancing user experience) and the content users produce. Reyman proceeded to blow my mind with a definition of data that I didn’t know: data and content/information are not viewed as the same thing (519). The data generated through content production is viewed as an “authorless object” (524), or one authored by technologies (nonhumans) alone. User consent requires only an agreement to the services when signing up, not an active role in understanding or mediating responsibilities of use (521). What Reyman argues is that data should be considered as a text coauthored with technologies, texts, and other users, which would reconceptualize it as living instead of as a sort of waste by-product of the content (523). Citing Krista Kennedy’s “Textual Machinery: Authorial Agency and Bot-Written Texts in Wikipedia”, Reyman makes visible the interaction between humans and nonhumans in data production “user data generation depends on users, on their interactions, participation, and production. It does not exist without them” (527).
Reyman tulimately draws our attention to the need to balance technology companies rights’ over user data (that they claim for the free services provided) with rights’ of the users, explaining that “With a balancing of users’ and technology companies’ rights over user data, the social and participatory Web could be nourished as a space that provides access to tools for participation and production, and also recognizes the value of human agency required for rich, meaningful social networks” (529).

In thinking about how we write ourselves and the social web through the social web, I’m wondering what means of balancing data are available beyond privacy fences (DoNotTrackMe and Ghostery) that can be built around browsing. I find myself thinking about the work the Creative Commons is doing to help users understand creating and interacting with web content; does data fall within Creative Commons domain? Is it an issue of outdated copyright law policies (seeing data as by-product rather than content) in need growing (more dynamically) with the times? I’m also curious to learn about more projects/texts created from data that could make visible what is too often dismissed as content debris—developing a meta awareness of metadata in interacting with the web.

useful and useless archives

/ Jana Rosinski / Leave a comment

In class this week, my role is the antithesis (I almost put a shopped image of myself with an evil Spock beard. Almost.) on the topic of archives in DH. Based on the readings, I have created the following matters of concern:

If one of the goals of DH work is to expand the audience beyond the academic sphere to the public sphere, how can archives be used to accomplish this? If ownership, authorship, and interpretation are factors, and DH makes strides to incorporate its readers as collaborators/builders/authors, how can the “public” (i.e. those outside of an academic institution physically or conceptually) gain access? Considering: location of archive, design of archive as user centered, permissions and data standards for collaborating, purpose of the archive project. Why should the public be interested? What are their stakes? What are they to gain?

Do we make archives? Do we make databases? Do we make collections? Do we make interfaces? Or do we make something similar, but just different enough? The conceptual usefulness in borrowing concepts come with shortcomings and pitfalls. With DH projects often blending and borrowing from established disciplines under the coherence of DH what might our work be complicating for the disciplines we borrow from?

How can DH address concerns of trained archivists, as expressed by Kate Theimer in Archives in Context and as Context, “What concerns me is that in the broadening of “archives” to extend to any digital collection of surrogates there is the potential for a loss of understanding and appreciation of the historical context that archives preserve in their collections, and the unique role that archives play as custodians of materials in this context”? Particularly when the conceptualization of the project and the design of the collection is often meant to expand as fluid, as ecology, as networks? If archive differs between DH and archivists, how does context hold up?

What are DH scholars doing to learn from archivists and librarians? How does a DH scholar interested in archives become an archivist-scholar?

What are the lifespans of DH archives? Who/what/where/how keeps them alive?

Are our archives just archives of our work?

Thinking of our readings made me recall Jeff and Jenny Rice’s 2012 CCCCs panel with Geoffrey Sirc, “Everyone Knows This is Nowhere: Writing in the Musical Age.”

Useless Archives: From Jeff Rice’s Useless Dylan

“The archives – in a university library, on a university website, in a university special collection – provides access to knowledge. Teaching the archives teaches a method for acquiring ideas, contextualizing ideas, and framing ideas anew. In the age of new media, archives, however, are institutional practices, and thus, they shape what is or is not important to a given research project. What about the peripheral items not featured in a given archive? How important are they to research?”

Do we view artifacts in an archive at a different scale? A different point of focus?

“How can I call “useless” what I value? Value is the wrong way to look at subject matter, whether musical, political, or some other item. Instead of value, I want the scraps, the outtakes, the speculation, the guesswork.  If I am to understand anything when I assemble a useless archive (and I do not promise any understanding), it is how the fragments of experience, when juxtaposed, allow insight previously prevented by what Vilem Flusser called the programmability of the political experience in the age of media”.

Can we make useless archives as serious scholarly pursuits? What are the potential consequences of the useless?

“The useless archive merely brings together. What I get from that combination, juxtaposition, linking, etc. depends. I may get a series of patterns. I may get a surface level “cute.” I may get affective response. I may get nothing. Whichever I get, that doesn’t mean that useless is “no good.” My archive is virtual. It is based on arrangement.”

How does arrangement get at/not get at selection—”archivists select materials for acquisition and accession” (Kate Theimer)?

archives: designing by/for the curious eye

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I was drawn to dwelling in Michael Neal, Katherine Bridgman, and Stephen J. McElroy’s “Making Meaning at the Intersections: Developing a Digital Archive for Multimodal Research” because one year ago I attended their panel “Developing a Digital Archive for Research in and beyond the University” at the Networked Humanities conference at the University of Kentucky. My initial preoccupation was turning to my memory of the conference (which is laden with blackout moments due to being nervous in such awesome company of people and ideas), and then my memory archived in my notebook of that time (this one suffered heavy water damage due to a poorly designed water bottle flooding my backpack), and then to pieces of the conference in web archives (hashtag was #nhuk) of tweets (on Storify) (TAGSExplorer) (Google spreadsheet), a handful of pictures, and blog posts that recapped presentations and reflected. Why I mention this process of scouring the web for traces of the conference is because my experience (my attention, my presence, my capacity) is limited. My memory of attending this conference, as deeply interested as I was, is already mostly fuzzy, although only a year later. See my (bad) notes below on the panel:

nhuknotesWhat I can recall is the panelists making a distinction between the good eye and the curious eye in looking, but the rest provided me little to reconstruct the presentation from until I could brush my own recollection (ideas, experience) against that of others. While I hesitate to call the stored Twitter exchanges an archive, its function during events/exchanges (like conferences) brought to mind questions of non-static archives, what it might mean for an archive to be fluid and responsive to user inquiry—How can archives be dynamic in design, almost heuristic like based on the user’s interests? How can such an archive function and be maintained?

In their Kairos piece, the authors detail the development of their postcard archive at Florida State University both digitally and physically with the specific goal of making their work visible—that is, how the archive is constructed (and in the process of construction) is not hidden behind the scenes of the collection. As archivist-researchers, they ask of their work:

  • How will researchers visiting this archive make meaning from within the infrastructure that we have constructed?
  • How can we continue to curate a digital space designed to enable growth over time at the same time that it hopes to reflect the voices and perspectives that are engaging the archive from both within and outside of the academy?

They explain that their approach to the archive’s infrastructure and metadata is resultant from visibility, or being able to see—the postcards, their shaping of the postcards, and the interactions that users have with the postcards:

“Our approach to archiving these material artifacts of everyday writing is very much a process of seeing, of learning to see, the multiple hands and voices that shaped and continue to shape these artifacts, even as they exist digitally in this open-source, expandable archive”.

This notion of seeing, of visibility, is of particular significance to the use of the archive as responsive to user contributions (through permitted registration with Omenka, where the archive is stored) and projects that users bring to the archive. The archivist-researchers explain at length how the archive is organized, a classification scheme that permits searching by date, place, subject matter, genre, publisher, etc. to account for the ecological nature of each postcard text. This design is to emphasize the potential of serendipity, or the unexpected, by carefully coded metadata that can permit such exploration and function heuristically for potential use (metadata categories that respond to the interaction between the artifact and the archivist). Designed this way, the archive is working to be flexible enough for research projects—that is more than one and undetermined from the outset:

“Each of the metadata fields we use to describe the artifacts (or a combination thereof) is a standard for arrangement, a potential filter. Insofar as a given digital representation of an artifact is composed by an arrangement of metadata relationships, the archive and its interface contribute to the modality and materiality of that artifact.”

This is where I wonder about their distinction between a good eye and a curious eye. The artifacts must be encoded with metadata to be searchable/accessible at all, and the authors explain this process, which evolved over time in interacting with the artifacts, but these negotiations were not just focused on interpreting the postcards as static artifacts to be classified within a static taxonomy, but on interpretations:

“As we negotiate the infinite levels of address possible for each postcard in our archive, we can attempt to preserve current and future readings of the card so that those readings will not be lost in history. In doing so, our job as archivists becomes one not only of cataloging, preserving, and making accessible artifacts, but also of cataloging, preserving, and making accessible interpretations of those artifacts, the multiplicity of meanings gleaned from and attributable to our archive.”

In returning to my exploration of the tweet “archive” of #nhuk and the design of this postcard archive, I wonder if the curious eye is a new standard in archive infrastructure, that an item is not just to be found because of the careful design of the good eye, but is to be found +. As if determining classification schemes based on categories and keywords didn’t seem difficult enough, how might they be designed for interpretation?

Databases

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This week, we are exploring databases in RCDH. This is an area of great interest to me to wonder/wander about, but to situate myself, I focused on reading on “The Notion of the Textbase: Design and Use of Textbases in the Humanities” by Charles Conney, Glenn Roe and Mark Olsen. I thought this reading would help me understand more about the role of metadata in textbase design and its effect on differing searchability. When I say I’m interested in databases, my knowledge of them is limited. I understand, at a very surface level, the word searching feature of databases working somehow with an algorithm that calls upon available text metadata through bibliographic and keyword information. I don’t understand the complexity of the algorithm at work, nor can I see “behind the scenes” of the database to know what text collection it is calling from and based on what criterion. My interest in databases is in better understanding these invisible operations and features, so my searching isn’t limited to

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and wondering how the tags are created, and what information from the text is being utilized for researching. Additionally, I had questions if there existed algorithms or schemes that were more exploratory in research; that is, ones that don’t seem to necessitate having search results or knowledge available before research begins.

To begin, textbases are a coherent collection of partly structured or unstructured digital documents that are assembled around unifying principles as thematic or generically similar. Cooney et al. define their goal as defining a selection of humanities databases built for textual analysis with particular attention to design principles that underlie their structure and inform their use. They argue that as textbases continue to develop, tools can offer alternatives beyond word searching which might allow the discovery of unseen connections across/between texts, the capability to trace ideas over a large collection or period, and to identify contextual and intertextual relationships of an individual text to any number of other texts. They also describe that textbases, utilized by digital humanities and electronic publishing, are hybrids of publishing and scholarly models that take up the concerns of presentation of text and the capability to support computer search through encoding. This design comes in three varieties: heavily encoded internal notation (works to preserve texts as historical documents), reliance on relational databases to manage metadata (works to understand texts and their creation and dissemination), and those of minimal level of markup (examines word use over large collections). The markup, or metadata, provides leverage or a handle for refining searches and permitting more complex retrieval tasks beyond a word search; so, that of author, title, date, genre, geographic area, historical context, etc. The amount of markup, in my understanding, can vary on a spectrum of retrieval to representation; this variance is due to the use of the texts – that of electronic publication or digital humanities research projects. Textbases created for textual analysis purposes are constructed to be used with computer assistance—the needs of “mundane” humanities research that looks across information at a massive scale quickly have les metadata encoded. Mixed mode textbases focus on word based data retrieval; indexing metadata is externally handled and associated with complex retrieval tasks to locate texts. These both operate on the automatic discovery of textual patterns based on word centered search, which is becoming increasingly limiting as text digitization and texbases grow – it reaches a threshold in navigability.  Conney et al. describe developing heuristic tools – machine learning, text mining, similarity algorithms, and clustering – that take form of one of three machine learning techniques: predictive, comparative, and clustering or similarity. Predictive and comparative techniques are systems designed to identify patterns or features associated with predetermined classes to distinguish categories in texts. They provide the example, though limited in its binary, of the algorithm that sorts spam email from non-spam email as distinguishing categories in a collection of texts. Clustering and similarity techniques work to identify documents or parts of documents that are most similar to one another rather than beginning from predetermined classes. They provide the example of this algorithm that identifies broad topics like Amazon recommendations. These are sensitive to smaller classes and functions with less orderly schemes, which are described as more “suited to the human” at the scale of a more defined collection. Conney et al. go into specific examples of intertextuality and similarity at work, which remain over my head for the time being in terms of accounting for the understanding of vector space models and n-gram word sequences, but end with the burden textbases will require attention to as the continue to grow—specialized language, specific encoding, and dedicated technical support to their creation and maintenance. They state that textbases will continue to improve to become better suited for humanities research in terms of sufficient tools, more narrow collections, and more focused research capabilities within text collections across entire networks.

While I understand better some of the language needed to talk about textbases and more intricate details about their scales of function, I’m still left wondering:

? if there are more textbase designs then these emphasized
? how the collections are formed and access to networks collections have
? how the exploratory and heuristic researching functions
? the relationship between metadata and patterns through textbase research
? if there are available textbases to explore (open source)
? are these at work in our scholarly publication and library databases

Defining DH*

/ Jana Rosinski / Leave a comment

This semester, I have the privilege of taking Rhetoric, Composition and Digital Humanities with Collin G. Brooke. We’re beginning class with defining DH, drawing from the following texts:

Matthew Berry, “Introduction” Understanding Digital Humanities (PDF)
Anne Burdick, et al., “A Short Guide to the Digital Humanities,” from Digital_Humanities (PDF)
Alan Liu, “The Meaning of Digital Humanities,” PMLA 128.2 (March 2013): 409–423.
(Alex Reid discussing Liu in “Digital Nonhumanities“)
Willard McCarty, “The Future of Digital Humanities is a Matter of Words.” from A Companion to New Media Dynamics (PDF)
Part I of Debates in the Digital Humanities, “Defining the Digital Humanities” (available online)
Staci Stutsman, “Digital Humanities vs New Media: A Matter of Pedagogy”
Part III of Debates in the Digital Humanities, “Critiquing the Digital Humanities”

Planting My Feet, or At Least Putting a Toe in a Direction

I began with Staci Stutsman, a doctoral student at SU studying film, new media, and popular culture, who through collected syllabi, works to look at the differences and similarities between DH and new media. I found this as a fruitful starting place to me as not only a doctoral student, but someone who, if I had any exposure to DH, I felt it would have come from my interests in new media. Stutsman (with the use of data visualization in the form of bar graphs) distinguishes the two (and this is a redux on my part):

DH: primarily hosted in English departments; looks to a small collective of theorists (scholar figure, see: Franco Moretti); defines itself through its methods; and works through distant reading and visualization approaches

new media: spread across departments (from Journalism to Education); casts its net further in terms of scholarly influence (scholar figure, see: Henry Jenkins); defines itself through its theory; and works through cultural studies approaches

The two, however, are compatible with overlapping interest areas. I was left with the impression that new media could develop through more tool based approaches, while DH could turn outward to other disciplines for topic content.

What is the Stuff of DH?

From my limited knowledge, I tend to think of DH as method focused—a way of doing that makes visible a question or pattern instead of starting from a point of inquiry. What is considered of significance to study closely (or distantly) I don’t feel can be answered, but Matthew Berry’s introduction, which works to understand DH through a computational turn that is still considerate of the human(ities), along with William McCarty’s careful exploration of future trajectory of DH as resonance (a metaphor that isn’t overly deterministic) made visible the complexity in the balance of who as the what—the delicate conversations about the (im)balance of human and nonhuman in DH work. When Berry poses the question of “what is human about computational sciences?” (patterns in data still require narrative to be understood – usable computation), I asked back, what is nonhuman about the humanities?

Digital (Non)Humanities

Reading Alan Liu along with Alex Reid helped articulate a space that I have neither the history nor the vocabulary to explain fully—what existed as a hesitation to label myself as a member of digital humanities because of the weight that humanities carries/d. Liu works to reveal the humanities core at digital humanities research as the “residual yearnings for spirit, humanity, and self—or, as we now say, identity and subjectivity.”; a sort of humanities 2.0 with slick new tools. Reid argues that DH might not only be troubling the tension that has existed between human and nonhuman (man and machine) but a new ontology abolishes the divide between humans and nonhumans as ontologically and epistemologically separate— “Regardless of whether one is convinced by such are argument about literary history, it is evidence that the controversy the digital humanities presents lies not in its assertion of the ontological divide between humans and nonhumans, or more precisely in its preference for the measurement of machines over the interpretation of humans, but rather in its erasure of that divide.”

I wonder if the what of DH is also the who and the how; and if DH has subdisciplines or factions as do other spaces in the field.

*I cannot define DH. I find myself still questioning the boundaries to discipline, field, method, theory.