the most important topics are which seems to consist mostly of stopwordspossibly with slight negative directiontopic which is clearly about bad reviewsfollowed by some genre-specific topics and and both of which seem to contain laudatory words it seems like lda mostly discovered two kind of topicsgenre-specific and ratingspecificin addition to several more unspecific topics this is an interesting discoveryas most reviews are made up of some movie-specific comments and some comments that justify or emphasize the rating topic models like lda are interesting methods to understand large text corpora in the absence of labels--oras hereeven if labels are available the lda algorithm is randomizedthoughand changing the random_state parameter can lead to quite working with text data