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Digital Humanities 2008 _____________________________________________________________________________ The ease of customization and the depth of customization are important to users if they use portals regularly. Second, users expect that a portal provides access to the breadth of services and resources they need for a domain of inquiry. Thus students expect a student portal to provide access to all the online resources they need as a student, from the library account to their course information. A portal should be just that -- a door into a domain. Is it possible for an IHP to be on the one hand easy to use (and customizable), and on the other hand truly provide broad access to resources? Is it possible that an IHP is too ambitious and would either be to complicated for humanists to use or not broad enough in scope to be useful? The answer in part lies in imagining an initial audience and conducting the usability studies needed to understand what they would expect. Thus we imagine an iterative process of designing for a fi rst set of users and redesigning as we learn more. This means a long term development commitment which is beyond most project funding. The challenges are enormous and we may be overtaken by commercial portals like Google or Yahoo that provide most of what humanists need. We believe, however, that the process of defi ning the opportunities and challenges is a way to recognize what is useful and move in a direction of collaboration. We hope that in the discussion modest fi rst steps will emerge. Bibliography centerNet: http://www.digitalhumanities.org/centernet/ Detlor, Brian. Towards knowledge portals: From human issues to intelligent agents. Dordrecht, The Netherlands: Kluwer Academic Publishers, 2004. Intute: Arts and Humanities: http://www.intute.ac.uk/ artsandhumanities/ TAPoR: Text Analysis Portal for Research: http://portal.tapor. ca VoS: Voice of the Shuttle: http://vos.ucsb.edu/ Beyond Search: Literary Studies and the Digital Library Matthew Jockers mjockers@stanford.edu Stanford University, USA Glen Worthey gworthey@stanford.edu Stanford University, USA Joe Shapiro jpshapir@stanford.edu Stanford University, USA Sarah Allison sdalliso@stanford.edu Stanford University, USA, The papers in this session are derived from the collaborative research being conducted in the “Beyond Search and Access: Literary Studies and the Digital Library” workshop at Stanford University. The workshop was set up to investigate the possibilities offered by large literary corpora and how recent advances in information technology, especially machine learning and data-mining, can offer new entry points for the study of literature. The participants are primarily interested in the literary implications of this work and what computational approaches can or do reveal about the creative enterprise. The papers presented here share a common interest in making literary-historical arguments based on statistical evidence harvested from large text collections. While the papers are not, strictly speaking, about testing computational methods in a literary context, methodological evaluations are made constantly in the course of the work and there is much to interest both the literary minded and the technically inclined. Abstract 1: “The Good, the Bad and the Ugly: Corralling an Okay Text Corpus from a Whole Heap o’ Sources.” Glen Worthey An increasingly important variety of digital humanities activity has recently arisen among Stanford’s computing humanists, an approach to textual analysis that Franco Moretti has called “distant reading” and Matthew Jockers has begun to formally develop under the name of macro-analysis. At its most simple, the approach involves making literary-historical arguments based on statistical evidence from “comprehensive” text corpora. One of the peculiarities of this activity is evident from the very beginning of any foray into it: it nearly always requires the creation of “comprehensive” literary corpora. This paper _____________________________________________________________________________ 13
Digital Humanities 2008 _____________________________________________________________________________ discusses the roles and challenges of the digital librarian in supporting this type of research with specifi c emphasis on the curation (creation, licensing, gathering, and manipulation) of a statistically signifi cant corpus. Because the arguments at stake are largely statistical, both the size of the “population” of texts under examination, and any inherent bias in the composition of the corpus, are potentially signifi cant factors. Although the number of available electronic texts from which to draw a research corpus is increasing rapidly, thanks both to mass digitization efforts and to expanding commercial offerings of digital texts, the variability of these texts is likewise increasing: no longer can we count on working only with well-behaved (or even well-formed) TEI texts of canonical literary works; no longer can we count on the relatively error-free re-keyed, proofread, marked-up editions for which the humanities computing community has spent so much effort creating standards and textual corpora that abide by these standards. In addition to full texts with XML (or SGML) markup that come to us from the model editions and exemplary projects that we have come to love (such as the Brown Women Writers Project), and the high-quality licensed resources of similar characteristics (such as Chadwyck Healey collections), we are now additionally both blessed and cursed with the fruits of mass digitization (both by our own hands and by commercial and consortial efforts such as the Google Library Project and Open Content Alliance), which come, for the most part, as uncorrected (or very lightly corrected) OCR. Schreibman, et al., 2008, have described University of Maryland efforts to combine disparate sources into a single archive. And a similar effort to incorporate “messy data” (from Usenet texts) into usable corpora has been described in Hoffman, 2007; there is also, of course, a rich literature in general corpus design. This paper will discuss the application of lessons from these other corpus-building projects to our own inclusion of an even more variant set of sources into a corpus suitable for this particular fl avor of literary study. This digital librarian’s particular sympathies, like perhaps those of many or most who participate in ADHO meetings, lie clearly with what we might now call “good,” “old-fashioned,” TEIbased, full-text digital collections. We love the perfectionism of “true” full text, the intensity and thoughtfulness and possibility provided by rich markup, the care and reverence for the text that have always been hallmarks of scholarly editing, and that were embraced by the TEI community even for less formal digital editions. Now, though, in the days of “more” and “faster” digital text production, we are forced to admit that most of these lessthan-perfect full-text collections and products offer signifi cant advantages of scale and scope. While one certainly hesitates to claim that quantity actually trumps quality, it may be true that quantity can be transformed into quality of a sort different from what we’re used to striving for. At the same time, the “macro-analysis” and “distant reading” approaches demand corpora on scales that we in the “intensely curated” digital library had not really anticipated before. As in economics, it is perhaps diffi cult to say whether increased supply has infl uenced demand or vice versa, but regardless, we are certainly observing something of a confl uence between mass approaches to the study of literary history and mass digitization of its textual evidence. This paper examines, in a few case studies, the gathering and manipulation of existing digital library sources, and the creation of new digital texts to fi ll in gaps, with the aim of creating large corpora for several “distant reading” projects at Stanford. I will discuss the assessment of project requirements; the identifi cation of potential sources; licensing issues; sharing of resources with other institutions; and the more technical issues around determining and obtaining “good-enough” text accuracy; “rich-enough” markup creation, transformation and normalization; and provision of access to the corpora in ways that don’t threaten more everyday access to our digital library resources. Finally, I’ll discuss some of the issues involved in presenting, archiving, and preserving the resources we’ve created for “special” projects so that they both fi t appropriately into our “general” digital library, and will be useful for future research. References Sebastian Hoffmann: Processing Internet-derived Text— Creating a Corpus of Usenet Messages. Literary and Linguistic Computing Advance Access published on June 1, 2007, DOI 10.1093/llc/fqm002. Literary and Linguistic Computing 22: 151-165. Susan Schreibman, Jennifer O’Brien Roper, and Gretchen Gueguen: Cross-collection Searching: A Pandora’s Box or the Holy Grail? Literary and Linguistic Computing Advance Access published on April 1, 2008, DOI 10.1093/llc/fqm039. Literary and Linguistic Computing 23: 13-25. Abstract 2: “Narrate or Describe: Macro-analysis of the 19th-century American Novel” Joe Shapiro Does the 19th-century American novel narrate, or does it describe? In 1936, Georg Lukács argued that over the course of the nineteenth century description replaced narration as the dominant mode of the European (and especially French) novel. What happens, we want to know, for the American novel? We begin with a structuralist distinction between the logics of narration and description: narration as the articulation of the events that make up a story; description as the attribution of features to characters, places, and objects in the story. We then set out, with the help of computational linguistics, to identify the computable sentence-level stylistic “signals” of narration and description from a small training sample (roughly _____________________________________________________________________________ 14
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