how to label topics automatically after applying LDA

Question

i have implemented LDA in python.now i want to label the topics whichever i got from LDA.

[(0, u'0.023*"alternate" + 0.023*"transfervisions" + 0.013*"tvcommunity"'), (1, u'0.026*"minimalism" + 0.026*"minimalist" + 0.018*"honking"'), (2, u'0.027*"videomaking" + 0.019*"python" + 0.019*"httpstcoc2ythrctki"')]

Answer 1

You might try using word vectors to average the top N words in a topic and then using the cosine similarity to find the closest word in the corpus?

Answer 2

Most creators of topic models assign the labels to the topics manually.

Automated labeling is perhaps possible for English language (with lots of rich language resources around), for some hints see these question on other Stackexchange sites and their answers:

• How to give name to topics created using LDA?
• Labeling documents with short text labels after topic modeling?
• Assigning meaningful cluster name automatically