Discovering Hot Topics On Social Network Based On Improving The Aging Theory

Thanh Ho, Duy Doan, Phuc Do


In this paper, we focus on discovering information on the social network to discover automatically the hot topics in real time. We suggest using aging theory for finding hot topics and using the tools for processing natural language and data processing model. We create a perfect general model. This system will help us find hot interesting topics on the social network in real time. With this idea, we will build a survey system which is the most accurate overview of the real world. If we can discover the interesting topics on the social networks, we can solve many problems in our present lives such as: to predict favored industry, the rising of consumer goods, Internet user community’s psychology, the objects that exchange information for each event, and to determine the direction of the social network.


Social network analysis; LDA model; SVM model; aging theory

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