Detecting two types of seasonal words using simple autocorrelation analysis

I analyzed frequency of word appearances in Japanese blogs and introduced the method which detects two types of seasonal words using simple autocorrelation analysis: one is for seasonal words with a specific day such as Christmas basically having sharp growth and decay around the peaking day characterized by a power function, and the other one is for seasonal words without a specific day like ski. The algorithm caught not only words which are easily understood as seasonal words such as Christmas and ski but also words which are not well known by everyone such as words related to local customs. We also found the number of seasonal words with a highest frequency on the day is widely distributed and in the case of seasonal words with a specific day the distribution follows a power law. These findings would give support to writers about seasonal topics and to suggest seasonal items for shop staff.