Topiquity

Web application for dynamic topic modelling on classical texts in the "Computing antiquity" project.

Setup

In order for the application to run properly you will need a dat/cleaned_corpus.csv in the working directory.
This file has to contain a table with one column being id_nummer containing the IDs of the texts, the other being text containing a whitespace-separated cleaned texts.

Debugging

For debugging purposes (or if you're just lazy to mess with docker) you may run the app by installing dependencies:

pip install -r requirements.txt

Then run the main script in the following fashion:

cd src && python3 main.py

The server will listen at localhost:8080, you are free to open it up in your browser.

Deployment

Both a Dockerfile and a docker compose default configuration is included in the repository, these might aid you in deploying the application to a webserver of some sorts, or just run the app on your computer in an isolated environment. It's easiest to get started by running the app in docker compose:

docker compose up

This will spin up a container and attach to localhost:7011

Known limitations

• DMM and LSI don't work particularly well, sometimes not at all, you should use LDA or NMF as things stand right now. A project-agnostic topic investigation platform might be developed in the near future.
• The code is heavily project-specific, if you want to use the application with a different corpus you will have to dig deep into the code.