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If you are new to digital humanities methods and scholarship like me, coming to a general understanding of what comprises the digital humanities can often feel like an overwhelming task. In this article, I survey a few introductory texts that help us grasp some of the basics defining the digital humanities and its goals.

First, “The Digital Humanities Manifesto 2.0” can be downloaded from Todd Presner’s blog Humanities Blast: Engaged Digital Humanities Scholarship. This text is vital to anyone new to the area, as it outlines what the digital humanities is, and is not, and why it is important. The manifesto, which has multiple authors and over 100 contributors, stresses that the digital humanities is “an array of convergent practices” rather than “a unified field,” one that involves digital tools and techniques but cannot merely be reduced to the digital (2). Contextualizing the digital humanities, it describes two waves of scholarship. In contrast to the first quantitative wave, the manifesto describes the second wave as “qualitative, interpretative, experiential, emotive, generative in character” and identifies the methodological strengths of the digital humanities as “attention to complexity, medium specificity, historical context, analytical depth, critique and interpretation,” maintaining that the use of digital toolkits supports the humanities’ key methodological advantages (2). Rather than discounting quantitative analysis, these authors see the potential of the second wave of the digital humanities in its capacity to “imagine new couplings and scalings” (2). The manifesto refers to a number of distinctive features characterizing the digital humanities: its “utopian core” and dedication to open source; the importance of co-creation and having a mass audience; the key role of process instead of final product; its potential global reach; and its questioning of disciplinary boundaries. Overall, these authors explain how the digital humanities serves “as an umbrella under which to group both people and projects seeking to reshape and reinvigorate contemporary arts and humanities practices, and expand their boundaries” (13 emphasis in original).

A second important text to consider when navigating digital humanities terrain is “A Short Guide to the Digital_Humanities,” the final section of Digital_Humanities by Anne Burdick, Johanna Drucker, Peter Lunenfeld, Todd Presner, and Jeffrey Schnapp. While its introduction is similar to the manifesto, it offers more historical background, identifying computation humanities as the precursor to digital humanities and highlighting the impact of the World Wide Web in its growth (SG3). In the next section, the authors present a series of questions and answers, where queries concerning the relationship between the digital humanities and more traditional forms of scholarship are addressed and explored. For example, the authors elucidate the use of projects, as both a structuring unit and as scholarship that projects. That is, “projects are projective, involving iterative processes and many dimensions of coordination, experimentation, and production” (SG4). They explain who is involved in such projects and how they are organized, funded, and (dis)continuous with “traditional forms of research and teaching in the humanities” (SG5). This section further investigates the relations and interconnections between the digital humanities and other institutions (e.g., libraries, museums, archives, institutions outside of the academy). Importantly, the authors then discuss the evaluative criteria in assessing digital scholarship (SG8); provide a list that can be utilized in writing a grant proposal (SG10); describe the basic skills necessary for undertaking digital humanities scholarship (SG12); identify the main learning outcomes for digital humanities research (SG14); and conclude by listing the cultural significance of such research (SG15).

In “What is Digital Humanities and What’s it Doing in English Departments,” Matthew Kirschenbaum jokes that articles contemplating “what is digital humanities” have become “genre pieces” (1). Yet, Kirschenbaum’s article contributes additional insights into the digital humanities. He first defines the digital humanities as “more akin to a common methodological outlook than an investment in any one specific set of texts or even technologies,” emphasizing that this methodological outlook can be both quantitative and/or qualitative (2). Second, he considers how the digital humanities operates as a “social undertaking,” involving “networks of people who have been working together, sharing research, arguing, competing, and collaborating for many years” (2). Similarly situating its roots in humanities computing, Kirschenbaum notes how in a span of five years it has grown from “a term of convenience” to the equivalent of a movement (4). Here, he attributes the role played by social media, such as Twitter, and the growing popularity among younger academics to experiment with digital technology in their research, especially in a period of academic change and uncertainty, to the development and acceleration of the digital humanities (4-5). He concludes:

Whatever else it might be then, the digital humanities today is about a scholarship (and a pedagogy) that is publicly visible in ways to which we are generally unaccustomed, a scholarship and pedagogy that are bound up with infrastructure in ways that are deeper and more explicit than we are generally accustomed to, a scholarship and pedagogy that are collaborative and depend on networks of people and that live an active 24/7 life online. (6)

Finally, of special interest to media historians, Bob Nicholson’s article on the digital turn forms a fascinating account of how “both qualitative and quantitative digital methodologies can be applied to the field of media history” (60). He begins by presenting some of the dominant debates on the pitfalls of digital research, which raise a number of concerns: missing important texts because they are not digitized, loss of access and materiality, proper contextualization, problems surrounding multiple remediation, and so forth. Turning to the advantages and new opportunities afforded by digital methods, Nicholson observes that they often lack the attention they deserve. By contrast, Nicholson’s discussion illuminates how digitalization permitted him to take new directions in his research, ask new questions, bring to light new connections, and map out “a relatively unexplored area of transatlantic popular culture” (71).

Other texts to consider include: Franco Moretti’s Graphs, Maps, Trees and Distant Reading; Matthew Jocker’s blog and his book Macroanalysis; Matthew Gold’s edited collection Debates in the Digital Humanities, and the full version of Digital_Humanities. Some useful web resources are the Journal of Digital Humanities, Digital Humanities Quarterly, and various blogs written by scholars in the area. Undoubtedly, becoming acquainted with digital humanities scholarship and methods is a fruitful but sometimes challenging task. The discussion here offers just an introductory glimpse into this expanding field.

Works Cited

Burdick, Anne, Johanna Drucker, Peter Lunenfeld, Todd Presner, and Jeffrey Schnapp. “A Short Guide to the Digital_Humanities.” Digital_Humanities. Cambridge, Mass: MIT Press,  2012. SG 1-16.

“Digital Humanities Manifesto 2.0.” 2009. Web. 8 May 2015.

Gold, Matthew, ed. Debates in the Digital Humanities. Minneapolis: U of Minnesota P, 2012.

Jockers, Matthew. Macroanalysis: Digital Methods and Literary History. Chicago: U of Illinois P, 2013.

—. Matthew L. Jockers. Blog. Web. 8 May 2015.

Kirschenbaum, Matthew G. “What is Digital Humanities and What’s It Doing in English  Departments?” ADE Bulletin 150 (2010): 1-7.

Moretti, Franco. Distant Reading. New York: Verso, 2013.

—. Graphs, Maps, Trees: Abstract Models for Literary History. New York: Verso, 2005.

Nicholson, Bob. “The Digital Turn.” Media History 19.1 (2013): 59-73.

Presner, Todd. Humanities Blast: Engaged Digital Humanities Scholarship. 2011. Blog. Web. 8 May 2015.

“To understand literature … we must stop reading books” (Moretti qtd. in Schulz). This provocative statement appears in Kathryn Schultz’s New York Times article about distant reading. To those unfamiliar with digital humanities scholarship and Franco Moretti’s approach of distant reading this statement might appear utterly bizarre. Reading such statements out of context has resulted in the perpetuation of various myths regarding digital humanities methods. To emphasize the potential benefits of digital humanities approaches, such as distant reading, cultural analytics, and macroanalysis, I have compiled a list of three dominant myths regarding distant reading in order to help deconstruct them.

1.  Distant reading leads to a loss of context.

If we are not actually reading the book, how can we properly contextualize the book and its meaning socio-historically? Moreover, in employing methods such as topic modeling or text mining, what Matt Burton refers to as “counting words,” how confident can we be that a significant loss of context does not result?

By discovering new interconnections between large collections of texts, digital humanities methods may in fact provide greater context. Moretti locates the problem of close reading in its reliance on an “extremely small cannon”; to get beyond the canon, he argues, distant reading is necessary (Moretti, “Conjectures”). At his Stanford University Literary Lab, Moretti utilizes computer programs to detect genre through “grammatical and semantic signals” (Schultz). His research demonstrates that genres “possess distinctive features at every possible scale of analysis,” formal elements that individuals may not discover without computer programs (Moretti qtd. in Schultz). Johanna Drucker similarly reveals how distant reading methods “expose aspects of texts at a scale that is not possible for human readers and which provide new points of departure for research.” She elaborates, “Patterns in changes in vocabulary, nomenclature, terminology, moods, themes, and a nearly inexhaustible number of other topics can be detected using distant reading techniques, and larger social and cultural questions can be asked about what has been included in and left out of traditional studies of literary and historical materials.” Moreover, undertaking a distant reading of ancillary texts, e.g., Ed Finn’s study of “a thousand book reviews” (3), produces a contextual background which allows the researcher to engage with a primary object of analysis. This leads me to the second myth.

2.  Distant reading ignores other materials surrounding the primary object of analysis.

Drucker defines distance reading as the processing of content in or information about “a large number of textual items without engaging in the reading of the actual text.” Computer analytics have the capacity to incorporate multiple discourses into a singular analysis, allowing researchers to elucidate the overlap between the popular, fan, industrial, and scholarly discourses surrounding the primary object of analysis. This permits researchers to explore and trace how particular ideas, values, practices have developed and spread within and between these ancillary discourses, highlighting objects, texts, and images, often disregarded in a close reading of an individual text or cultural artifact. For example, in “Becoming Yourself: The Afterlife of Reception” Finn explores the social lives of books and uses both professional and Amazon customer book reviews of David Foster Wallace as his primary datasets, studying and mapping the multiple networks of texts that appear as a way to investigate Wallace’s location in the literary marketplace.

Another way we can investigate these ancillary discourses is through topic modeling. David Blei explains how topic modeling, where a topic is defined as a pattern of “tightly co-occurring terms,” uses computer algorithms to identify thematic structures concealed in great masses of texts in order to “summarize, visualize, explore, and theorize about a corpus” or among multiple collections. In turn, this shift towards what Moretti refers to as “the archive of the Great Unread” (Distant 181) works against canonization and its issues of value.

3.  Distant reading displaces close reading.

Matthew Jockers prefers the term macroanalysis to distant reading, comparing it to macroeconomics and its focus on the big picture. Relating this to Pierre Bourdieu and his study of cultural economy, we can reposition distant reading as a technique to analyze the broader field of cultural production in which the cultural artifacts we study are produced, circulated, consumed, and given value. In this respect, it becomes less a matter of distance than focus; that is, it is a methodology which uncovers the broader workings of cultural artifacts often downplayed or completely ignored in a close reading of the object or text. As Jockers contends, “The most fundamental and important difference in the two approaches is that the macroanalytic approach reveals details about texts that are for all intents and purposes unavailable to close-readers of the texts.”

This interpretation is similar to the one held by Moretti, who maintains:

Distant reading: where distance, let me repeat it, is a condition of knowledge: it allows you to focus on units that are much smaller or much larger than the text: devices, themes, tropes—or genres and systems. And if, between the very small and the very large, the text itself disappears, well, it is one of those cases when one can justifiably say, Less is more. If we want to understand the system in its entirety, we must accept losing something. We always pay a price for theoretical knowledge: reality is infinitely rich; concepts are abstract, are poor. But it’s precisely this ‘poverty’ that makes it possible to handle them, and therefore to know. This is why less is actually more. (“Conjectures”)

Yet, for Moretti the debate over close and distant reading, and the questions it raises—“are they complementary, compatible, opposite, do I really want people to step reading books, etc.”—holds little interest (Distant 137).

Overall, Jockers points out that his macroanalytic approach is just one of many methods of gaining and assessing information about a cultural artifact, the results of which are “not of lesser or greater value to scholars.” He argues persuasively, “It is the exact interplay between macro and micro scale that promises a new, enhanced, and perhaps even better understanding of the literary record.” Myths, such as the ones presented here, often arise due to a perceived threat to established methods and approaches to media history or literature. However, it is important to critically evaluate the potential contributions of digital methods and thus view them as complementary to more traditional methods.

Works Cited

Blei, David. “Topic Modeling and Digital Humanities.” Journal of Digital Humanities 2.1 (2012): n. pag. Web.

Burton, Matt. “The Joy of Topic Modeling: A Bag of Words by Matt Burton on the 21^st of May 2013.” n. pag. Web.

Drucker, Johanna. “Distant Reading and Cultural Analytics.” UCLA Center for Digital Humanities: Intro to Digital Humanities. Concepts, Methods, and Tutorials for Students and Instructors. n. pag. Web.

Finn, Ed. “Becoming Yourself: The Afterlife of Reception.” Stanford Literary Lab Pamphlet. 15 Sept. 2011. Web.

Jockers, Matthew. “On Distant Reading and Macroanalysis.” Author’s Blog. 1 July 2011. n. pag. Web.

Moretti, Franco. “Conjectures on World Literature.” New Left Review 1 (2000): n. pag. Web.

—. Distant Reading. Brooklyn: Verso, 2013.

Schultz, Kathryn. “What is Distant Reading? The New York Times. 24 June 2011. n. pag. Web.

As media historian Bob Nicholson points out in his article “The Digital Turn,” while the downfalls of the digital turn in the humanities have been mapped out, affirmed, and reasserted, the “advantages of digitalization have been treated as too obvious to require explanation” (61). In this respect, it is important to draw attention to the possible strengths of a digital humanities approach. Here are twelve reasons for media historians to consider digital methods.

1. The Big Picture

There is a limit to the amount of individual texts, objects, sounds, and moving and still images that a researcher is able to read, watch, listen, and examine. Digital tools and methods have the capacity to account for a great mass of cultural artifacts, quantifying it into data, visualizing it on a grand scale, and allowing the researcher to identify patterns in the data that otherwise would be lost.

2. A Shift from Close to Distant Reading

Correspondingly, looking at a bigger picture and considering a complex mass of objects, texts, sounds, and images, some of which might be ephemeral, creates a shift in the scale of research from close to distant reading. In Graphs, Maps, Trees, Franco Moretti questions what happens when (literary) historians alter their gaze, comprehending distance not as a barrier, but as a way to reveal new forms of knowledge and understanding. Thus, for Moretti, distant reading, the use of quantitative methods to help identify patterns and elucidate interconnections across multiple texts, is the antithesis of close reading (1).

3. Production of New Forms of Knowledge

Digital tools create new sets of quantitative data, generally unfamiliar to many humanities scholars, to be interpreted, mapped, and visualized. Working with data sets has the potential to produce and represent new forms of knowledge, including new historical critiques, assessments, and narratives.

4. Visualization: Graphs, Maps, Trees

Digital tools produce visualizations to map and comprehend large amounts of data across space and time. In “Digital Visualization as a Scholarly Activity,” Martyn Jessop notes how digital visualization can be administered to any data and used in all areas of the humanities (291). For Jessop, the introduction of space through data visualization permits researchers to investigate patterns and interconnections not visible in written language (284). Furthermore, Nicholson asserts: “Whilst it is important to recognize the limitations of such an approach – it does not, after all, reveal the meaning of the texts it counts – it provides a useful way to visualize broad cultural trends and identify areas for closer inspection” (69).

5. Accentuation of Circulation through Data Visualization

Importantly, visualizing such forms of data can reveal the dynamic movement of cultural artifacts through time and space, illuminating new connections between particular objects of study (i.e., trade, fan, and academic discourses) and elucidating larger trends that may easily be overlooked.

6. Visual Comparisons

Creating visualizations of multiple data sets allows for comparisons. For example, as demonstrated by Eric Hoyt in the “Welcome to Project Arclight” video, a researcher can undertake a comparative analysis using visualizations that graph the differences in the career arcs of two actors.

7. New Questions Raised

Digital tools and approaches not only assist in answering our research questions but also lead to the exploration of unchartered territory, the drawing of previously unseen connections, and the formation of innovative questions that may not otherwise arise within a traditional media history methodology.

8. A Challenge to the Primacy of Text

A digital humanities approach encourages humanities researchers to both situate our objects of study as data and to contemplate the implications and potential problematics of such action. Doing so poses a challenge to the very primacy of text and textual analysis.

9. Collaboration

Since data can be interpreted in multiple ways and in various contexts, it can help foster collaboration among researchers. Moretti emphasizes its collaborative value, as data “are ideally independent from any individual researcher, and can thus be shared by others, and combined in more than one way” (5).

10. Communication and Accessibility

In his article “The Digital Inhumanities?” Scott Selisker argues that the biggest impact of digital humanities lies in “changing the ways scholars communicate their work to the public” (n. pag.). Digital humanities projects often maintain dedication to open source. Therefore, the digitization of archival materials, which are often kept hidden away under lock and key, has a huge impact on accessibility for scholars and the general public alike. Furthermore, projects like the Betham Project are eliciting help from the public through crowd-sourced transcription (see Cohen).

11. Comprehensive not Representative Sample

By focusing on general structures and patterns and moving away from individual texts, digital tools and methods can encourage a more comprehensive rather than representative sample, allowing for a shift away from canonical texts and received dominant histories.

12. Acceptance of the Unknown

Digital methodologies and distant reading uncover “the limits of what we can know about culture in the digital age” (Selisker n. pag.). Hoyt astutely points out that as a researcher this involves acknowledging that not everything can be digitized, accepting that materials will and do get lost, embracing various other complications that arise in algorithmic research, and reflecting upon the implications of this within the research process.

In examining the reasons why a digital approach may be useful to media historians it becomes apparent that digital tools not only have the capability to alter the ways in which media historians study media history, but they also “have the potential to transform the content, scope, methodologies, and audience of humanistic inquiry” (Burdick, Drucker, Lunenfeld, Presner, and Schnapp 3). The work of the Roy Rosenzweig Center for History and New Media (RRCHNM) provides strong evidence for the benefits of using digital tools in the study of media history, reflecting many of the reasons listed here. Over the last twenty years RRCHNM researchers have developed new digital software and methods (e.g., Serendip-o-matic, Omeka) to “democratize history” (n. pag.). In this respect, RRCHNM reinforces the value of digital tools and methods and

their capacity to help “incorporate multiple voices, reach diverse audiences, and encourage popular participation in presenting and preserving the past” (n. pag.). While the RRCHNM is one example of how digital forms open up media history methods and approaches, a variety of possibilities lie ahead and await our engagement.

Works Cited

“About.” Roy Rosenzweig Center for History and New Media. 2014. 14 Nov. 2014.

Burdick, Anne, Johanna Drucker, Peter Lunenfeld, Todd Presner, and Jeffrey Schnapp. Digital_Humanities. Cambridge, Mass: MIT Press, 2012.

Cohen, Patricia. “Scholars Recruit Public for Project.” New York Times. 27 Dec. 2010. Web.

Hoyt, Eric. “Welcome to Project Arclight.” Online video clip. Vimeo, 13 May 2013. 17 Nov. 2014.

Jessop, Martyn. “Digital Visualization as a Scholarly Activity.” Literary and Linguistic Computing 23.3 (2008): 281-293.

Moretti, Franco. Graphs, Maps, Trees: Abstract Models for Literary History. New York: Verso, 2005.

Nicholson, Bob. “The Digital Turn.” Media History 19.1 (2013): 59-73.

Selisker, Scott. “The Digital Inhumanities?” “Two Rebuttals to ‘Literature is not Data: Against Digital Humanities.’” LA Review of Books. 5 Nov. 2012. Web.

In 2012, Stephen Marche wrote a scathing article about big data and digital humanities in the LA Review of Books, arguing passionately: “literature is not data.” Positioning digital humanities as nothing more than “instant titillation” and just another “next big thing,” he locates its fundamental problem as the attempt to treat literature like data. For Marche, literature is the antithesis of data and regarding it otherwise results in the removal of taste, value, distinction, and refinement, merely reducing the cannon to a stack of books. Clearly, a digital humanities approach to literature has struck a chord with Marche, and his article may be representative of a deeper fear of data, the quantification of literature and other objects of study, as well as the broader digital humanities altogether. But perhaps he is misguided in his approach to the digital humanities, distracted by its supposed shortfalls rather than recognizing its benefits. In his article “Big? Smart? Clean? Messy? Data in the Humanities,” Christof Schöch similarly notes the suspicion of data and quantitative methods from scholars. He connects this distrust to “the apparent empiricism of data-driven research in the humanities [which] seems at odds with principles of humanistic inquiry, such as context-dependent interpretation” (n. pag.). How can we jettison this fear of data in the humanities and maintain the critical analytical stance we value?

Kim Crawford’s six myths of big data may be an apt place to start. Crawford calls attention to the fact that big data is not new but rather has become more ingrained in everyday life, making it more visible and harder to ignore. Moreover, she illuminates how data is something that is created and imagined, not an objective truth or “fact,” and thus, it always needs to be contextualized. In his response to Marche’s article, Scott Selisker emphasizes how data is not something that is likely to replace the interpretation of individual texts or to “dehumanize” literature (or other cultural artifacts), but can supplement and strengthen such analyses. He asserts: “They don’t threaten the individuality of literary works, but rather help us return to those literary works with more information at hand” (n. pag.). Taking into account the great mass of ephemeral texts, objects, sounds, and moving and still images that fall outside the cannon poses significant methodological challenges. Utilizing digital tools and methods, and thus coming to terms with data and quantitative research, may be one such direction, assuming one pays head to Crawford’s cautions. When we shift our perspective toward conceiving distant reading, data, and digital methods as potentially advantageous rather than an encumbrance to analysis, we can begin to understand how such methods might uncover new forms of knowledge and pose new research questions. As Christine Borgman elucidates in Scholarship in the Digital Age, recognizing the importance of data is much more than a digital issue. It is a theoretical, methodological, and social one as well.

Another way of ameliorating the fear of data is by gaining a greater grasp of what constitutes data. Schöch proposes the following definition:

Data in the humanities could be considered a digital, selectively constructed, machine-actionable abstract representing some aspects of a given object of humanistic inquiry. Whether we are historians using texts or other cultural artifacts as windows into another time or another culture, or whether we are literary scholars using knowledge of other times and cultures in order to construct the meaning of texts, digital data add another layer of mediated into the equation. Data (as well as the tools with which we manipulate them) add complexity to the relation between researchers and their objects of study.

Understanding what data is, how it functions, what its limits are, and what it reveals can be viewed as the first steps towards meaningful engagement with data and digital humanities. For a more detailed discussion of the benefits of digital methods and data visualization, look to my next article: “Why Digital Humanities? 12 Reasons for Media Historians.”

Works Cited

Borgman, Christine. Scholarship in the Digital Age: Information, Infrastructure, and the Internet. Cambridge, Mass: MIT Press, 2007.

Crawford, Kim qtd. in Quentin Hardy. “Why Big Data is Not Truth.” The New York Times. 1 June 2013. Web.

Marche, Stephen. “Literature is not Data: Against Digital Humanities.” LA Review of Books. 28 Oct. 2012. Web.

Schöch, Christof. “Big? Smart? Clean? Messy? Data in the Humanities.” Journal of Digital Humanities 2.3 (2013): n. pag. Web.

Selisker, Scott. “The Digital Inhumanities?” “Two Rebuttals to ‘Literature is not Data: Against Digital Humanities.’” LA Review of Books. 5 Nov. 2012. Web.