A Spatio-Temporal Approach to the Discovery of Online Social Trends
作者： Harshavardhan Achrekar , Zheng Fang , You Li , Cindy Chen , Benyuan Liu
DOI: 10.1007/978-3-642-22616-8_40
关键词:
摘要: Online social networks (OSNs) have become popular platforms for people to interact with each other in the cyber space. Users use OSNs talk about their daily activities, mood, health status, sports events, travel experiences, political campaigns, entertainment and commercial products, among things. Conversations between users on an OSN site could reflect current trends that are of great interest importance individuals, businesses, government agencies alike. In this paper we design develop a comprehensive system collect, store, query, analyze data effective discovery online trends. Our consists three parts: (1) collection engine; (2) spatio-temporal database storing, indexing, querying data; (3) set analytical tools trend discovery. We demonstrate effectiveness our using recent result predicting seasonal flu Twitter data.
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