• Readings for Next Classes
  • For Tuesday
    • Benjamin Schmidt, “Vector Space Models for the Digital Humanities” (2015)
    • Saptarashmi Bandyopadhyay et al., “Word Embedding Demo Tutorial” (2022) — Note: The actual demo accompanying this tutorial about word embeddings (or word vectors) is assigned for the second part of Practicum 5.
  • For Thursday
    • Ryan Heuser, “Word Vectors in the Eighteenth Century” (conference proceedings abstract) (2017)
      • Optional: If you are interested, you may wish to read Ryan Heuser’s series of blog posts about word embedding linked from this page on his blog (with individual posts on “Concepts,” “Methods,” “From Fields to Vectors,” and “Semantic Networks”).
  • Due Thursday, Nov. 3rd: Word Embedding Exercise

Student outputs

Andrew Piper, excerpt from “Topoi (Dispersion),” in Enumerations: Data and Literary Study (2019)  — read only pp. 66–75

And yet, despite the growing body of work on topic models, no one has stopped to ask the question “What is a topic?,” either in the classical rhetorical sense or in the computational one. If we have this new way of deriving semantic significance from texts at a large scale, how does it fit within the longer philosophical and philological traditions of understanding “topics”? What, in other words, do these lists of words mean? (67)

… I will begin with an overview of the history of thinking about topics, from Aristotle to Renaissance commonplace books to nineteenth-century encyclopedism. Understanding how topic modeling fits within this longer tradition of deriving coherent categories of thought from a surplus of information — where there has always been a surplus from a single human perspective — will help us see how computation has a distinct pre-computational past. (68)

Commonplace Books

• Kelsey McKinney, “Social media: Nothing new? Commonplace books as predecessor to Pinterest” (2015)
• John Locke, page from one of his commonplace books.
  

Andrew Piper

Reading topologically provides a new way of attending to the form of language, this time through an attention to the latent quantities of words. It allows us to envision how figure and concentration serve as an essential foundation of human thought, and that their opposites, dispersion and formlessness, are equally essential for the process of intellectual change….Topological reading makes visible the way topics are neither firmly bounded objects stable through time, the transcendentals of philosophical thought, nor clearly evolving genealogical units, the elements of Begriffsgeschichte [history of ideas, or conceptual history] that move coherently from one form to another across linear time.
Studying topics in this way allows us to see how topics ultimately contain a sense of their own otherness, that, like the computational topics used to model them, each topic contains within itself the potentiality of all other topics in the topical space. (70)

At the same time, the disambiguation between topics in topic models is complemented by a greater degree of ambiguity within topics….
The computational topic, by contrast, incorporates that openness within itself. Rather than group statements under a single keyword or phrase, it organizes a heterogeneity of statements under a complex semantic field. It operates according to the principle of many to many. (74)

Ferdinand de Saussure, Course in General Linguistics (1916)  – read pp. 114-117, 123-27

Claude Lévi-Strauss, “The Structural Study of Myth” (1951) and Savage Mind (1962)

Jacques Derrida, “Structure, Sign and Play in the Discourse of the Human Sciences” (1966):

J. [John] R. [Rupert] Firth, “A Synopsis of Linguistic Theory, 1930-55” – read sections III-IV (pp. 7-13)

The basic assumption of the theory of analysis by levels is that any text can be regarded as a constituent of a context of situation or of a series of such contexts…. The context of situation according to this theory is not merely a setting, background, or ‘back-drop’ for the ‘words’. The text in the focus of attention on renewal of connection with an instance, is regarded as an integral part of the context, and is observed in relation to the qther parts regarded as relevant in the statement of the context. (7)

The placing of a text as a constituent in a context of situation contributes to the statement of meaning since situations are set up to recognize use. As Wittgenstein says, ‘the meaning of words lies in their use.’ The day to day practice of playing language games recognizes customs and rules. It follows that a text in such established usage may contain sentences such as ‘Don’t be such an ass!’, ‘You silly ass!’, ‘What an ass he is!’ In these examples, the word ass is in familiar and habitual company, commonly collocated with you silly–, he is a silly–, don’t be such an–. You shall know a word by the company it keeps! One of the meanings of ass is its habitual collocation with such other words as those above quoted. (11)

It will then be found that meaning by collocation will suggest a small number of groups of collocations for each word studied. (13)