I've a list of 1,300 news events, represented by only three terms coming from running LDA topic model on thousands of tweets. Here's some of them as an example:
['manchester,bony,city', 'attack,claims,responsibility', 'police,officers,nypd', 'goal,arsenal,liverpool', 'test,pakistan,sunday', 'obama,ukraine,merkel', ...]
I need to group them in more general domains (Politics, Sport, Health, Economy, etc.).
Which kind of clustering algorithms could I use (in Python)?
Or maybe, can I use LDA topic model, even if I don't have documents but only three words?