15. The non-transitory computer-readable storage medium according to claim 10 , wherein the instructions further comprises: after the second word set is formed, from a pre-established word tree, acquiring words related to a hot word contained in the second word set and relevancies of the words related to the hot word contained in the second word set, wherein the word tree is pre-established through a text clustering algorithm; calculating hot degrees of the words related to the hot word contained in the second word set according to the relevancies of the words related to the hot word contained in the second word set and a hot degree of the hot word contained in the second word set; adding the acquired words related to the hot word contained in the second word set into the second word set; and classifying, through a text clustering algorithm, words in the second word set into word subsets.
15. The non-transitory computer-readable storage medium according to claim 10 , wherein the instructions further comprises: after the second word set is formed, from a pre-established word tree, acquiring words related to a hot word contained in the second word set and relevancies of the words related to the hot word contained in the second word set, wherein the word tree is pre-established through a text clustering algorithm; calculating hot degrees of the words related to the hot word contained in the second word set according to the relevancies of the words related to the hot word contained in the second word set and a hot degree of the hot word contained in the second word set; adding the acquired words related to the hot word contained in the second word set into the second word set; and classifying, through a text clustering algorithm, words in the second word set into word subsets. 16. The non-transitory computer-readable storage medium according to claim 15 , the selecting topics from a community topic set according to the second word set comprises: calculating a hot degree of each topic contained in the community topic set according to hot degrees of hot words contained in the second word set; and determining topics with top hot degrees in the community topic set as hot topics, wherein the number of the topics with top hot degrees is equal to a third preset threshold, or determining topics with hot degrees greater than a third preset hot degree in the community topic set as hot topics.