So if you are wondering about the acronyms of this reading concordances in the 21st century,

which of course is quite a mouthful to spell out every single time, that's why we have

settled on RC21. And what we want to do in this talk is to introduce you to some called

strategies that can be used to analyze concordances, which you can think of as basically a corpus query

result presented in a particular manner. We'll be showing you and introducing you to some

concordances to read throughout this talk. And as Marianne has already introduced, this will be

supported with the tool that is being developed in the course of this project. Here we'll be

focusing on a running example, which is a case study from a case study in body part nouns in

19th century novels. And in this particular talk, we'll be focusing on the form, the word form hands

in novels by Charles Dickens. Now, before we tell you more about this, we would like you to read

concordances. So if you haven't seen a concordance before, this is basically what it is. And I will ask you

just to take a look at this and to see whether you can see anything about how Dickens is using the word

hands in this context, if there's anything you pick up on.

Would you like to connect with another person?

There's really no right or wrong answers, I just want to collect a few impressions.

Where the hands are, in his pocket, behind the direction.

I don't know if that's what you were implying, but his and her, like the front?

It's always, when it's her hands, it's always relating to him.

Yes, very good. Thank you very much. We've already collected a number of things that we will come back to throughout the talk.

And as I say, there's really no correct or incorrect answers here. But I hope that you get an impression.

Okay, there are some things we can pick up on quite intuitively here without really having any particular

background without knowing the novels necessarily. Of course, we could just go ahead and read the entire concordance.

You might be wondering, what's the point? Maybe just read through the novels at that point,

which of course in the case of Transdicts, we could actually do. However, there are some issues with this.

So it doesn't scale well, obviously, as soon as we move to larger corpus, we actually need some other strategy to identify patterns.

And also not all patterns are obvious. And what I showed you right now is also not just a random instance of lines that you happen to stumble across while opening your corpus.

But it was after applying a very dedicated algorithm that we actually identify these.

And even then you can see it's not it's not as immediately obvious what what we're looking for.

So we actually need some strategies to go about this more systematically, which basically boiled down to rearranging the corner slides in different ways.

We have an inventory of strategies shown here and we'll show you a few of them in applied examples later on.

But before that, I should go into that.

And in order to work with concordances, we are developing a Python library called Plexicon, which obviously comes from flexible concordancing.

And we want to create a Python library that would support concordance reading and make it reproducible, accountable, transparent and flexible.

You see that these epithets, they're actually very, very important for our purposes because we want to make concordance reading a science.

We want to make it want to supply the researchers with proper tools.

And we know that we actually are going a bit against the trend here because people nowadays are more fascinated by large language models and chat GPT where you just input your concordance and ask, ask it to analyze it and to spit out the result.

No, that's not what we actually want to achieve.

We want concordance reading to be a scientific procedure where every single individual step is clearly documented, where we can trace what the researchers have done with their concordance and how they have arrived at the results using understandable and clearly documented algorithms.

And this is the aim of our Plexicon Python library that will be used for reading concordances.

I must stop here and warn you a little bit about what our Plexicon actually is not.

So it is not a corpus management tool as a whole.

As our project is focused on reading concordances, we do not do many things that belong to corpus linguistics like collocation analysis or keyword analysis.

This is outside the scope of our project.

We are really focused on providing researchers with readable and interpretable concordances.

So do not expect like collocations coming out from our tool, from our library.

So all this should be done outside and also visualization and quantitative analysis is also something that is supposed to be handled outside of Plexicon by a host step that uses it as a module.

And another thing I want to warn you about is that it is work in progress.

So for those of you who use Python, you can see no link here on the screen.

And if you try typing like something like PIP install Plexicon, you will get nothing for the time being.

Even though if you are technically advanced, you will be able to get a link to the current development version from the Jupyter notebook I'm going to show a little bit later.