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Social media keeps growing and providing us with rich sources of information to understand our everyday lives, customs, and culture in the form of periodic topics. This paper proposes a method of detecting periodic topics based on autocorrelation using the time series of the document frequencies of keywords. To deal
The topic correlation judgment algorithm based on weight and threshold is proposed as for the problem that Web pages which are closely related to the given topic may be neglected due to not all keywords given by the users in the pages when users retrieve the topic they desire on the Internet. The algorithm retrieves
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.