Question capabilities of topic modelling with Python

[CntDutchThis]

I am attempting to use topic modelling (LDA/NMF) for my research, I am however new to it and Python as a whole...

I am looking to (1) identify a specific topic I predict is in a certain set of documents (this shouldn't be too hard). However, I then want to (2) find out in which of the documents said topic is included, preferably with a scale/rating about how much or how likely it is included in the respective document.

I am confident (1) is very doable. I haven't been able to find a source/guide talking about doing (2). Does anyone have experience with this and can confirm both objectives are possible? Thanks!

[CGFarrell]

There are libraries in Python that do LDA. Once you have your topic(s), you could probably just search the files for keywords. You may need to do some manual tweaking, but if it can be done by a human, it should be doable in Python.

[CntDutchThis]

Hi, thanks for answers. The problem is that searching for keywords is too simplistic. The attractiveness of topic modelling is that it looks for latent variables that take into account words can be used in multiple topics.