Hey fellow data lovers!
I have a data modelling problem for a clustering analysis that I can't wrap my head around. Perhaps I'm thinking to advanced and I should simplify my analysis.
I have 2 data sets:
- Persons with their properties:
- Conversations and their properties:
- Sentences of the conversations
- Keyword of a sentence + it's frequency
- Polarity of the sentence (pos, neg or neutral)
I would like to cluster terms that have the same polarity for a group of people. Eg. male persons between 20 and 35 speak positively about economy and neg about privacy Eg. male persons from BE, NL and DE speak neg about climat changes.
Problem is that I need to cluster multiple terms for an undefined group of people. For one term (eg. privacy) it would be 'easy' to determine the properties of the different segments as this is a classification problem. As I would like to cluster multiple terms together, I'm strugling to model my data as this means I have multiple records per person (they can talk about multiple terms).
Assumption: you can assume I have one record per person per term.