Identifying Dynamic Topics of Interest across Social Networks
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 8
Abstract
Information propagation plays a significant role in online social networks, mining the latent information produced became crucial to understand how information is disseminated. It can be used for market prediction, rumor controlling, and opinion monitoring among other things. Thus, in this paper, an information dissemination model based on dynamic individual interest is proposed. The basic idea of this model is to extract effective topic of interest of each user overtime and identify the most relevant topics with respect to seed users. A set of experiments on real twitter dataset showed that the proposed dynamic prediction model which applies machine learning techniques outperformed traditional models that only rely on words extracted from tweets.
Authors and Affiliations
Mohamed Salaheldin Aly, Abeer Al Korany
Keywords
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- EP ID EP376010
- DOI 10.14569/IJACSA.2018.090845
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