Designation of Situation Model in Twitter using Maximal Frequent Sequences

Hashtag is definitely one of the most significant features of Twitter which now is spread all over the social networking services. It can serve different functions, and one of the most important is the designation of situation models. Using the method of Maximal Frequent Sequences we proved that the main idea of all data of one hashtag can be described in two or three phrases as a summary processed using the given method. We demonstrate how the recognition of situation models can be done automatically and fast. Also this method can be used for analysis of hashtag combinations and reconstruction of concepts based on the results of 1-grams and 2-grams, as we presented in detailed example of analysis of the following hashtags: #GalaxyFamily, #RussianMeteor, #Grammys and #10Dec hashtags.