- Hi David! - Hi Simon!
This is a brief introduction for students, or potential students, to our course:
Foundations and Applications of Humanities Analytics.
And I think the opening question might be:
why is a philosopher of science - you're a philosopher of science -
why is a philosopher of science leading this course?
That's a great question, Simon, and I think it really comes down to
by taking an epistemological approach,
also you might call it an epistemology first approach,
to humanities analytics, sometimes called digital humanities,
or cultural analytics, what we're doing something very different from other
introductions to this field, that might be offered to a PhD student
or a scholar in the humanities, which is our core audience.
And what we're doing there, is rather than saying:
"here are some tools, go ahead and use them
to do quantitative work in the digital humanities"
we're starting with the question:
"what is the epistemology of this new science?" Right?
What is the process by which this new way of thinking about human cultural output
allows us to form justified beliefs and, possibly, even knowledge, if you think
there's such a thing as knowledge. I'm personally a little skeptical.
So that's really where I think a philosophy of science,
and a philosophical approach, more broadly, to humanities analytics
really has some value. So that would be my answer to that question.
Yeah, I mean this is interesting, David. The idea of beginning first with:
"How are we going to go about knowing what's the nature of the subject itself?"
That's something I think that's been difficult for those of us coming from the
technical side, scientific side, coming in.
Because the criteria for what it means to get something right is very different.
The kinds of things we're interested in knowing are very different
in the sciences versus the humanities,
and part of this work, to me, has always been:
How are we getting things right for both sides of the aisle? As it were.
Yes, I think that's right. And I think that what's important to note
is this is a very new field of inquiry, so in that case it's to be putting
together this kind of course, and to be trying to address this.
Not by "Here's how to plug in your corpus into an LDA topic model",
but rather to start a little earlier.
We will get to things like that. But to start a little earlier by saying
Here is this new science what are its foundations?
What are its goals? What are its interests?
I think is a really cool way to start.
And I say "new science", it's also a new approach to the humanities.
So what you say about hitting both sides of that aisle is exactly right.
Again, our focus is really on an audience of humanities scholars
and people whose interest is, first and foremost, in some area of
cultural output by human beings, and taking it from there to try and see
how we can use some quantitative and computational tools to make new progress
in these areas and gain new insights.
One of the things that's always struck me is that, in the end, I've never done
a project in cultural analytics that doesn't involve a collaboration
between people whose PhDs were in technicals, M fields,
and people who write monographs for a living, right?
One of the things that I remember, the first time I pitched this to
an audience of historians, and work we had done for an audience of historians,
someone in the back said "How many books of history do we have
to throw out, because of what you've just done?"
And, what he was really after, of course, was: what kind of knowledge is this?
What have you done? How does this bear on a practice that is
much, much older, in fact, than any of the empirical sciences.
I think that's right, and I think it highlights what I see as
a really important goal of this course, perhaps, maybe, THE goal of this course
for students, which is: we want to use this course to train humanities scholars
to get to a point where they can be collaborators
within digital humanities projects.
So I think you're exactly right, that sort of humanities analytics,
digital humanities project works best when you have a team that includes
a humanist and someone from a more computational and quantitative background.
At least those two. And then often more, even three or four, authors is really
a really nice number, often.
And that's really what we're trying to do here. Is trying to bring people who come
from more traditional humanities backgrounds, to that place where they
can approach someone, who maybe works in a quantitative science department
or a computer science department, and say:
"I've got a really cool question, that I think can be answered
by computational analytics techniques. Let's work together.
But let's not have it be totally siloed off, where I'm just doing the humanism
and you're just doing the computation." But let's actually work together and find
a nice meaty part of that Venn diagram that intersects.
So that we can really bring something new to the table, rather than just two people
doing two things there in space then mashing that together into a paper.
Well this is one thing that comes up now. This is now something you can actually do
as scholars. We've always had people in the humanities doing quantitative analyses.
I was just reading that Alistair McKinnon, the philosopher in the '60s,
did a stylometric study of Kierkegaard's Pseudonyms-
- oh wow! - which is quite fun, so I'm not quite
sure what to make of it - he takes the ratio of logarithms,
which I'm unhappy about.
But it seems like these team efforts are increasingly part of the culture
in the humanities. We have coming up, as part of this course, guest lecturers.
All of them are going to be talking about how this work gets into the scholarship
in the humanities. Another question is: how can we do this
work and not have it be a one-off, kind of fun thing you did on the side, but how can
this actually help someone build a scholarly profile - build a body of work
that will last a long time.
That's a really good point, and I think I'm glad that you mentioned the guest
lecturers in this course, because if someone's watching this introductory
video and thinking I'm just going to have to listen to these two for 10 - 14 weeks...
no, that's not the case! We've got a great lineup of guest lecturers, and just three
to highlight now are: Lauren Klein, Richard Jean So, and Julia Lefkowitz.
Each of which has been given the brief to present something that's meant to be a
little bit inspiring. We're going to be talking a lot about foundations, a little
bit of applications, as well, giving students the nuts and bolts of what we
see as a good humanities analytics scholarship. But that's different from
seeing a finished project, and while we will present some finished projects,
I think it's really great to bring someone else in,
in Julia's case, for instance - here's someone who wrote a PhD thesis quite
recently, in a digital humanities area, and can really walk people through how
that project works, and how she actually got from a humanities background to
actually doing a fully-fledged scholarly project in digital humanities.
Similarly, with Lauren Klein's work, I think we get a really great sense of how
her really deep interest in core humanities topics - like power and how power has
worked through history and American history - led to this sort of quantitative
project that yields some really interesting insights about who was leading
and who was following in the language of abolitionist papers. And then, finally, in
reading Richard Jean So's presentation, I think there's just such innovation in
the way he finds sources, to think about storytellers are interacting with COVID-19
and this area of pandemic, that we are obviously still in. So I think
between those three projects, and there are other guest lecturers as well, but
between those three projects, it's just a really nice sense of what people are
going to get out of this course, beyond just the nuts and bolts. Sort of seeing
how they can see their own research through the same prism that these
guest lecturers have.
Yeah, I think one of the key things that we've been doing here is - there's plenty
of really fun theory one can do about what it would mean to investigate an aesthetic
experience, an historical event, quantitatively. We're really focused on
getting people up and running in their own projects. Our goal here is things that
people can immediately start applying. Maybe they're not beginning a PhD thesis
on something they've learned in lecture 2, but getting people to the place where they
can start doing this. They don't have to buy our particular epistemology in order
to get going. One thing - one of the big features of this course, that we've been
funded to do, which is particularly exciting, is run - in parallel with the
lectures each week - is run an online discussion forum, where people will be
able to exchange ideas, talk about things.
We'll have a TA, Zachary Donovan, who'll be working on assignments that people have,
joint writing projects, ways for which people can, not only, try to solidify the
understanding they have from the lecture, but also, hopefully, build collaborations.
Build networks and relationships with other people who are following along.
Yeah - as much as is possible within an online course format, we do see
one of our metagoals for this course is to build the next generation of
humanities analytics scholars. And a big part of that is creating connections
because for everything we can teach, and everything we can lecture about,
there's no substitute for the sort of organic connection that happens when
two scholars come together and realize that there's a common interest,
and a common interest in investigating that interest. And that would the greatest
if we can facilitate some of that. I did want to go back to one thing you said
about "we don't need you watch lecture 2 here and go off and write a PhD thesis..."
I think one of the nice things about the humanities analytics paradigm is because
the unit of a "project" tends to be a paper, rather than necessarily a full
book, it is possible for someone to come away from this course, have an idea,
build it up a little bit more, and develop it in a reasonable amount of time that
isn't going to totally sidetrack perhaps the more traditional humanities
scholarship. So if you're listening to this and thinking:
"well, I have the book that I know I want to write"
and it's ultimately a qualitative project in my field of expertise, that isn't
meant to keep you from doing that. It's augmenting your scholarship. It's not
taking anything away from your other scholarship, because I think we're both
people who love the humanities, and don't want to see what we're doing as
in any way in competition for resources or research time with more traditional
work in humanities. It can be, and often is, excellent, so we don't want to see
ourselves as in competition there at all.
Yeah, I think this is a great thing to bring up.
There's different ways this kind of work can get into scholarship.
So, our guest lecturers, by and large, are talking about cultural analytics
projects from start to finish. In Lauren Klein's case, and Richard Jean So's case,
these wind up being papers in some of the top humanities journals, certainly.
There's lots of venues for people to publish those works,
the Journal of Culture Analytics, for example, but at the same time, I think
this course could serve as a way for people to supplement the research they're
doing. This could be some tools that would enter in a single chapter of
a larger monograph, a larger dissertation.
So, this can be a supplement to work that one's already doing.
But this can also be a jumping off place to do original work from start to finish.
A piece of work where the qualitative and the quantitative are
inextricably tied together.
That's a really point. I do want to emphasize though, because we're going
a lot down this path of thinking about the relevance of our course for its core
audience, which is a sort of PhD student in the humanities - that's how we've
designed the course - but that isn't to the exclusion of other people getting a lot
out of this course. We've always said that while we do have this core audience,
it's also the case that we would love for people, whether it's more senior scholars,
or maybe an undergraduate who's just very interested, or someone who works
as a librarian, or something like that, to get more into humanities analytics
foundations and techniques. Certainly nothing we've said here should be to the
exclusion of someone like that getting as much as possible out of this course.
And maybe it is just doing more scholarship, or maybe it's just having
a broader understanding of this world and how it works.
Or on the undergraduate side, maybe thinking differently about the kind of
academic trajectory they'd like to pursue going forward.
I think all of that is possible, and the course is designed to have that flexibility
as well. I think the assignments are broadly written enough, and broadly
pitched enough, that anyone with an interest in humanities analytics
can get a lot out of this course. I would hope.
I mean, so yeah, our mandate from the National Endowment for Humanities
is broad. There's no particular career stage that you need to be at.
There's no particular career stage we expect you be at.
For many people the unit of work is the journal paper, certainly in the sciences.
For many people it's the monograph.
But also for many people it's the website.
It's the undergraduate class.
Certainly, humanities analytics is something that's showing up in
the liberal arts colleges, just as much as the research universities.
What is our mandate? Our mandate is to enable people, to empower people,
to do great scholarship, of any form, at the cutting edge -
of whatever is actually going on when we open these books, but also open
our laptops at the same time.