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"')]
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:
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?