2. The storage medium of claim 1 , wherein the method further comprises: computing a first ratio of a number of hot users that sent electronic messages including the object entity and the keyword, and a total number of users who sent electronic messages including the object entity and the keyword; computing a second ration of a number of hot users that sent messages including the object entity to a total number of users who sent messages including the object entity; and computing a score indicating a likelihood of co-occurrence of of each keyword and the object entity in the identified sets of messages sent by the hot users, by dividing the first ratio by the second ratio.
2. The storage medium of claim 1 , wherein the method further comprises: computing a first ratio of a number of hot users that sent electronic messages including the object entity and the keyword, and a total number of users who sent electronic messages including the object entity and the keyword; computing a second ration of a number of hot users that sent messages including the object entity to a total number of users who sent messages including the object entity; and computing a score indicating a likelihood of co-occurrence of of each keyword and the object entity in the identified sets of messages sent by the hot users, by dividing the first ratio by the second ratio. 3. The storage medium of claim 2 , wherein, the score for each keyword is compared with a second threshold value to determine whether the keyword is either positive or negative training data for the object entity.