SMC Seminar on ANALYZING EVOLUTION OF RARE EVENTS

#Analysis

ANALYZING EVOLUTION OF RARE EVENTS THROUGH SOCIAL MEDIA DATA

Mr. Xiaoyu Lu, ECE, NJIT

Time: 2pm, April 10, 2018

Place: ECEC 202, NJIT

Recently, some researchers have attempted to find a relationship between the evolution of rare events and temporal-spatial patterns of social media activities. Their studies verify that the relationship exists in both time and spatial domains. However, few of them can accurately deduce a time point when social media activities are most highly affected by a rare event. Thus, it is difficult to characterize an accurate temporal pattern of social media during the evolution of a rare event. This work pays an attention to intensity of information volume and proposes an innovative clustering algorithm-based data processing method to characterize the evolution of a rare event by analyzing social media activities. Furthermore, novel feature extraction and fuzzy logic-based classification methods are proposed to distinguish and classify event-related and unrelated messages. Our case study focuses on a hurricane named Sandy that occurred in 2012. Twitter data collected around it is used to verify the effectiveness of the methods. The results not only verify that a rare event and social media activities have strong correlations, but also reveal that they have a time difference. This is conducive to investigate the temporal pattern of social media activities.

Bio-sketch: Xiaoyu Lu (S’14) received the B. S. degree from Nanjing University of Technology, Nanjing, China, in 2011 and the M. S. degree from New Jersey Institute of Technology, Newark, NJ, USA, in 2015. He is now pursuing the Ph. D. degree in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA. His current research interests include Petri nets modeling of microgrids, Petri nets applications in power systems, and power management and smart grids.

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• 323 BLK Blvd
• Newark, New Jersey
• United States 07102-1982

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• Starts 01 April 2018 07:47 PM UTC
• Ends 09 April 2018 07:47 PM UTC
• No Admission Charge

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