Abstract
SummaryWith the development and popularization of Internet big data, the cyber world nearly parallels to the real world to reflect social hot event. However, the multi‐source and heterogeneity features of reality data lead to incompleteness and unreality based on Internet data. To solve the above issues, we propose Event Space Model (ESM) for event analysis by multi‐viewer. In the model, each event is mapped into Network Public Opinion Data Space (OS) and Actual Behavior Data Space (BS). In addition, we propose an Event Starting Point Discovery Algorithm (ESPDA) to effectively detect starting point of event and to identify the representation of event trajectory in OS and BS. The experimental results prove that the ESM represent event from multi‐viewer, while the ESPDA intensively identify events and improve recall and precision of starting point of event. Copyright © 2016 John Wiley & Sons, Ltd.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Concurrency and Computation: Practice and Experience
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
