Thus our questions this week involve both what it's like to read a work of scholarship on an unfamiliar idea in draft form and the substance of the work.
Process questions:
- What do they mean by “live writing”?
- What strategy did you use for reading this project?
- Would you write in public like this?
- What is going on behind their scenes?
Substance questions:
- What is their Big Idea?
- Can we imagine together the kinds of questions historians will want to ask with Big Data?
- What do they mean by the “macroscope” metaphor? Why not a telescope?
- Would you feel comfortable working with an “open notebook”? With live writing?
- Do you accept the claim that we (as historians) need to understand the search algorithm?
- What is “big data”? What do you think of their definition?: “If it’s more data that you could conceivably read yourself in a reasonable amount of time, or that requires computational intervention to make new sense of it, it’s big enough!”
- Who is the audience for this project?
- What can you learn by working with big data that you can’t without it?
- What do you need to learn to do to work with big data?
- How is normalization different from tokenization?
- What kinds of questions can you imagine yourself asking with big data?
- Why do they argue that Big Data does not herald an epistemological transformation for historians?
- What is topic modelling, and what would you use it for? What uses could you put Paper Machine to?
- What is network analysis and what might you use it for?
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