CFP: The overview of the clustering methods on the example of Fanfiction tags

I applied with this talk to PyCon Slovakia, but was not accepted.

Title: The overview of the clustering methods on the example of Fanfiction tags

Abstract:

There are a lot of ways to group the data together: from topic models, factor analysis, k-clustering and many more. Each with their own specifics.

But in actual analysis, it is hard to know, which one to use and how to tune it for each case. Most of them also have parameters, that effect the final result.

In this talk, I would like to show their differences, by checking how different methods and settings change the results on the example of the clustering of Fanficton tags.

Bio:

I am a software engineer at LeanIX. I come from a cognitive science and economics background, so I am more likely to be interested in how to use programming to find out the answer to the social science questions, data analysis and automation, then going into the nitty picky details about kubernetes. I also interested in how people and technology relate to one another.