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Tuesday, March 20

  1. page Chad Seader edited {photo.JPG} I'm interested in exploring what opportunities the digital humanities present for l…
    I'm interested in exploring what opportunities the digital humanities present for literacy education in prison. Are there methods, practices, and ideas within digital humanities that can make writing and reading more relevant to incarcerated men and women? Can digital interfaces, web-based software, and digital archives host prison writing and help make that writing known to audiences outside of the prison in mainstream society? Furthermore, can past discussion in digital humanities help us address the institutional and bureaucratic challenges that hinder the implementation of digital and web-based tools in prisons?
    Twitter: TBD
    Tumbler: TBD
    Blog:Seader Digital Humanities

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Wednesday, February 28

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Wednesday, September 2

  1. page Syllabus (Bare Bones) edited CCR 733: Rhetoric, Composition, and Digital Humanities Schedule of Activities Before Classes S…

    CCR 733: Rhetoric, Composition, and Digital Humanities
    Schedule of Activities
    Before Classes Start:
    Robin Sloan, Mr Penumbra's 24-Hour Bookstore (Amazon)
    Charles Soule, Strange Attractors (Amazon)
    Week 1 Introduction to Course
    Monday, January 13
    Course Agenda
    There are no required readings for our first meeting, but I do recommend setting up some sort of blogspace (Wordpress, e.g.) in advance, as well as a Twitter account if you don't already have one. We will spend some time discussing this site, and the various roles that social media will play in the course. If you have questions about this prior to the actual course, feel free to contact me.
    Week 2 - No Class Meeting (MLK)
    Week 3 Definition
    Monday, January 27
    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" (You should at least skim this)
    Week 4 Database
    Monday, February 3
    Charles Cooney, et al. "The Notion of the Textbase: Design and Use of Textbases in the Humanities." LSDA
    Sharon Daniel, "The Database: An Aesthetics of Dignity." from Database Aesthetics (PDF)
    Ed Folsom, "Database as Genre: The Epic Transformation of Archives." PMLA 122.5 (Oct 2007), 1571-1612 (includes responses).
    Christiane Paul, The Database as System and Cultural Form: Anatomies of Cultural Narratives." Database Aesthetics (PDF)
    Geoffrey Sirc, "Serial Composition." Rhetorics and Technologies (PDF)
    Collin G Brooke, " Databases, Data Mining" and "Personal Patterns: Mapping and Mining {LF4excerpt.pdf} " from Lingua Fracta (PDF)
    Week 5 Archive
    Monday, February 10
    Casey Boyle. Low-Fidelity in High-Definition: Speculations on Rhetorical Editions. RDH
    Johanna Drucker, "The Book as Call and Conditional Texts."
    Tarez Samra Graban, Alexis Ramsey-Tobienne and Whitney Myers. In, Through, and About the Archive: What Digitization (Dis)Allows. RDH
    Michael Neal, et al. Making Meaning at the Intersections. Kairos
    Liza Potts. Archive Experiences: A Vision for User-Centered Design in the Digital Humanities. RDH
    Jenny Rice and Jeff Rice. Pop Up Archives. RDH
    Kate Theimer, "Archives in Context and as Context." JDH 1.2 (2012).
    Week 6 Metadata
    Monday, February 17
    Tarez Samra Graban, "From Location(s) to Locatability: Mapping Feminist Recovery and Archival Activity Through Metadata." College English76.2 (Nov 2013): 171-193. (PDF)
    Kieran Healy, "Using Metadata to Find Paul Revere."
    Richard McNabb, “Making the Gesture: Graduate Student Submissions and Expectations of Journal Referees.” Composition Studies, 29.1 (2001): 9-26. (PDF)
    Geoffrey Nunberg, "Google's Book Search: A Disaster for Scholars." CHE, August 31, 2009.
    Jessica Reyman, "User Data on the Social Web: Authorship, Agency, and Appropriation." College English 75.5 (May 2013): 513-522. (PDF)
    Jentery Sayers, et al., Standards in the Making
    Week 7 Algorithm
    Monday, February 24
    Kevin Brock, One Hundred Thousand Billion Processes: Oulipian Computation and the Composition of Digital Cybertexts
    James Brown, "Making Machines"
    Tarleton Gillespie, "The Relevance of Algorithms"
    Stephen Ramsay, Reading Machines: Toward an Algorithmic Criticism
    Annette Vee, "Understanding Computer Programming as a Literacy." Literacy in Composition Studies 1.2 (2013): 42-64.
    James Brown, Making Machines, the website (you don't need to read it, but check out the first chapter there)
    Lisa Gye, "From Information Literacy to Procedural Literacy—Or, How to Be Literate in Algorithmic Culture." Ctrl-Z 3 (2013).
    Week 8 Microscopy
    Monday, March 3
    Matthew Jockers & Julia Flanders, "A Matter of Scale"
    Seth Long, "Text Network and Corpus Analysis of the Unabomber Manifesto." Feb 12, 2013
    Elizabeth Losh. Nowcasting/Futurecasting: Big Data, Prognostication, and the Rhetorics of Scale. RDH
    Geoffrey Rockwell, "What is Text Analysis, Really?" LLC 18.2 (2003): 209-219. (PDF)
    Greg Urban, "The Once and Future Thing" from Metaculture. (PDF)
    Ampersand (Lindsey)
    Donald Foster, Author Unknown (PDF)
    Patrick Juola, "Rowling and "Galbraith": an authorial analysis" Language Log, July 16, 2013.
    Ben Zimmer, "Decoding Your Email Personality." NYT, July 23, 2011
    Ben Zimmer, "The Science that Uncovered J.K. Rowling's Literary Hocus-Pocus." WSJ, July 16, 2013.
    Week 9 Mesoscopy
    Monday, March 17
    Carol Berkenkotter & Thomas Huckin, "Conventions, Conversations, and the Writer" (PDF)
    David Hoffman and Don Waisanen. "At the Digital Frontier of Rhetorical Studies: An Overview of Tools and Methods for Computer-Aided Textual Analysis" (RDH)
    Dan Wang, "Is There a Canon in Economic Sociology?" Accounts 11.2 (2012): 1-8.
    Topic Modeling (this is a cluster of blog posts that should provide a good intro to TM)
    Megan R. Brett, Topic Modeling, A Basic Introduction
    Andrew Goldstone and Ted Underwood, What can topic models of PMLA teach us about the history of literary scholarship?
    Lisa M. Rhody, Topic Modeling and Figurative Language
    Scott Weingart, Topic Modeling for Humanists: A Guided Tour
    Issue 2.1 of the Journal of Digital Humanities on Topic Modeling (some add'l TM readings here)
    Ben Blatt, "A Textual Analysis of //The Hunger Games//." Slate, 20 Nov 2013.
    Jonathan Goodwin, Recent Developments & Interpreting Topics (+ more) (Jonathan has been topic modeling Rhet/Comp journals)
    Dec 2013 issue of Poetics, special issue on Topic Modeling (available through our library)
    Responses to Poetics issue from Andrew Perrin and Laura Nelson (these are good, short, measured/skeptical takes on TM)
    Conference on College Composition and Communication (CCCC) - March 19-22
    Week 10
    Monday, March 24
    Because so many of you are traveling to CCCC this year, there won't be a reading assignment for this week. However, we will meet and share progress on the semester-long assignments (the Portfolio and Project as explained under Expectations). At this point in the semester, you should have made good progress on the Portfolio (enough to consider this a soft deadline for it) and have a pretty solid idea of what you'll be doing for the Project. You should come to class prepared to share your progress on both assignments, and you should be far enough along that the class can provide you with substantive feedback.
    Week 11 Macroscopy/Macroanalysis
    Monday, March 31
    Matthew Jockers, Macroanalysis
    Week 12 Macroscopy
    Monday, April 7
    Erez Aiden & Jean-Baptiste Michel, excerpt from Uncharted: Big Data as a Lens on Human Culture (PDF)
    Nelya Koteyko. Corpus-Assisted Analysis of Internet-Based Discourses: From Patterns to Rhetoric. RDH
    Franco Moretti, "Conjectures on World Literature." NLR
    Gregory Crane, “What Do You Do With a Million Books?” D-Lib Magazine12.3 (2006).
    Jean-Baptiste Michel et al., “Quantitative Analysis of Culture Using Millions of Digitized Books,”Science331.176 (2011): 176-182.
    Ted Underwood, “How Not To Do Things with Words,” blog post, The Stone and the Shell, 25 August 2012.
    Mark O'Connell, Bright Lights, Big Data: Culturomics and Results-Based Reading, The New Yorker, 20 March 2014.
    Ben Zimmer, Google's Ngram Viewer Goes Wild, The Atlantic, 17 October 2013.
    Week 13 Networks
    Monday, April 14
    Phillip Gochenour, "Nodalism." DHQ
    James Porter. "Rhetoric in (as) a Digital Economy." Rhetorics and Technologies (PDF)
    Mark C. Taylor, "From Grid to Network." from The Moment of Complexity (PDF)
    Duncan Watts, from Six Degrees. (PDF - 2 chapters)
    Could Nate Silver Predict How Good Your Pumpkin Pie Will Be? NPR. 19 November 2012.
    Peter Olson, Graphing the Marvel Universe (video)
    Week 14 Visualization
    Monday, April 21
    Tanya Clement, "Text Analysis, Data Mining, and Visualizations in Literary Scholarship." LSDA
    Johanna Drucker, "Graphesis: Visual knowledge production and representation" (PDF)
    Johanna Drucker, "Humanities Approaches to Graphical Display." DHQ
    Martyn Jessop, "Digital Visualisation as a Scholarly Activity" LLC 23.3 (2008): 281-293. (PDF)
    Krista Kennedy and Seth Long, "The Trees Within the Forest: Extracting, Coding, and Visualizing Subjective Data in Authorship Studies." RDH
    Stéfan Sinclair, et al., "Information Visualization for Humanities Scholars." LSDA
    Max Black. from Models and Metaphors
    Virginia Kuhn, "Process and Processing: Methods for Discovery and Representation in Data"
    Jen Jack Gieseking, "Opaque is Being Polite: On Algorithms, Violence, & Awesomeness in Data Visualization"
    Josh Honn, "Visualizing Elision" (discusses Drucker & Gieseking)
    Week 15 Maps/Graphs
    Monday, April 28
    Morgan Currie, "The Feminist Critique: Mapping Controversy in Wikipedia." UDH
    Kieran Healy, "A Co-Citation Network for Philosophy."
    Brad Lucas and Drew Loewe, "Coordinating Citations and the Cartography of Knowledge." The Changing of Knowledge in Composition (PDF)
    Franco Moretti, "Network Theory, Plot Analysis."
    Derek Mueller, “Grasping Rhetoric and Composition by Its Long Tail: What Graphs Can Tell Us about the Field’s Changing Shape.” CCC 64.1 (Sep 2012): 195-223. (PDF)
    Anne Stevens and Jay Williams, "The Footnote, in Theory." Critical Inquiry
    Franco Moretti, "Graphs, Maps, Trees" (this is the first of three essays that eventually turned into his book by the same title.)
    Last Day of Classes - Tuesday, April 29
    Last Day to submit work for course - Monday, May 5

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Saturday, November 29

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Saturday, April 26

  1. page Weingart, Scott. Topic Modeling for Humanists, A Guided Tour. edited Reading Notes: CCR 733 Chelsea Carroll Scott Weingart: “Topic Modeling for Humanists: A Guided T…
    Reading Notes: CCR 733
    Chelsea Carroll
    Scott Weingart: “Topic Modeling for Humanists: A Guided Tour”
    Citation: Weingart, Scott. “Topic Modeling for Humanists: A Guided Tour.” The scottbot irregular. Scott Weingart, 25 July 2012. Web blog.
    Abstract: This is a blog post written to provide an introduction on topic modeling from a humanist perspective:
    “It’s that time again! Somebody else posted a really clear and enlightening description of topic modeling on the internet. This time it was Allen Riddell, and it’s so good that it inspired me to write this post about topic modeling that includes no actual new information, but combines a lot of old information in a way that will hopefully be useful.”
    Keywords: Topic modeling; topics; LDA; humanities; humanists; tool(s);
    Key Cites:
    In order to provide a “guided tour,” Weingart cites and provides links to a variety of other introductions to topic modeling by Jockers; Templeton; himself; Underwood; Chen; Riddell; and Blei.
    Crucial Quotes:
    “The algorithm is constrained by the words used in the text; if Freudian psychoanalysis is your thing, and you feed the algorithm a transcription of your dream of bear-fights and big caves, the algorithm will tell you nothing about your father and your mother; it’ll only tell you things about bears and caves. It’s all text and no subtext. Ultimately, LDA is an attempt to inject semantic meaning into vocabulary; it’s a bridge, and often a helpful one.”
    “It is a simple and powerful tool, but notice that none of the automated topics have labels associated with them. The model requires us to make meaning out of them, they require interpretation, and without fully understanding the underlying algorithm, one cannot hope to properly interpret the results.”
    How long will it take, and what developments will need to take place, before topic modeling can be more accessible to users without programming knowledge/expertise?

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  2. page Rhody, Lisa. Topic Modeling and Figurative Language. edited Reading Notes: CCR 733 Chelsea Carroll Lisa Rhody: “Topic Modeling and Figurative Language” Cit…
    Reading Notes: CCR 733
    Chelsea Carroll
    Lisa Rhody: “Topic Modeling and Figurative Language”
    Citation: Rhody, Lisa M. “Topic Modeling and Figurative Language.” Journal of Digital Humanities 2.1 (2012). Web.
    Abstract: “Understanding how topic modeling algorithms handle figurative language means allowing for a similar beautiful failure — not a failure of language, but a necessary inclination toward form that involves a diminishing of language’s possible meanings. However, the necessarily reductive methodology of sorting poetic language into relatively stable categories, as topic modeling suggests, yields precisely the kind of results that literary scholars might hope for — models of language that, having taken form, are at the same moment at odds with the laws of their creation.
    In the following article, I suggest that topic modeling poetry works, in part, because of its failures. . . .
    By locating ‘figurative language’ as an aspect of address for topic modeling, I choose to constrain my consideration of poetic texts and agree to a caricature of poetry that hyper-focuses on its figurative aspects so that we can better understand how topic modeling, a methodology that deals with language at the level of word and document, can be leveraged to identify latent patterns in poetic discourse.”
    Keywords: Textual Analysis; methodology; topic modeling; topics; poetry; text; LDA;
    Key Cites:
    Blei, David. “Probabilistic Topic Models.” Communications of the ACM 55.4 (2012): 77–84. Print.
    Witmore, Michael. “Text: A Massively Addressable Object.” Debates in the Digital Humanities. Minneapolis, MN and London: University of Minnesota Press, 2012. 324–327. Print.
    Witten, Ian H, Eibe Frank, and Mark Hall. Data Mining: Practical Machine Learning Tools and Techniques. Third Edition. New York: Elsevier Science, 2011. Web. 25 Mar. 2013.
    Crucial Quotes:
    “To a certain extent, textual scholarship implies a double bind: no one can address a text at all of its possible levels simultaneously, and yet, by constraining our understanding of what a text is, we make a caricature of it.”
    “Topic models (and LDA is one kind of topic modeling algorithm) are generative, unsupervised methods of discovering latent patterns in large collections of natural language text: generative because topic models produce new data that describe the corpora without altering it; unsupervised because the algorithm uses a form of probability rather than metadata to create the model; and latent patterns because the tests are not looking for top-down structural features but instead use word-by-word calculations to discover trends in language.”
    “Few questions will find “answers” here. Instead the hope is to uncover new methods for addressing enduring humanities questions that we might fruitfully ask about figurative language with LDA.”
    “I wondered, could topic models detect gendered language, tropes, or the language of stillness in ways that “we can learn” about the genre more broadly?” – Learn being the key word: how can we employ topic modeling to learn about a corpus?

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