Database Reference
In-Depth Information
Generally speaking, the application of big data of online SNS may help to better
understand people's behavior and master the laws of social and economic activities
from the following three aspects:
Early Warning
: to rapidly cope with crisis if any by detecting abnormalities in
the usage of electronic devices and services.
Real-Time Monitoring
: to provide accurate information for the formulation of
polices and plans by monitoring the current behavior, emotion, and preference of
users.
Real-Time Feedback
: acquire groups' feedbacks against some social activities
based on real-time monitoring.
The application of big data of online SNS involves three core technical prob-
lems:
Data Model
: Most traditional SNS data models are based on the static mode and
specific analytical algorithms, and are not amenable for effective computation
with data in the PB and higher scales. On the other hand, SNS analysis usually
implements multi-dimensional complex relevant analysis on dynamic data. New
theories and models need to be investigated to bridge this gap.
Data Storage and Management
: The existing Internet based storage management
methods mainly support big data storage and rapid query. However, the existing
approach does not effectively support the analytical computation of big data
of online SNS, featuring high correlation, dynamic variability, and multi-
dimensional evolution, etc. Therefore, new storage and management methods
need to be developed.
Data Analysis
: The existing analytical methods on big data of SNS are mainly
based on single-dimensional attribute, with insufficient accuracy. On the other
hand, SNS analysis, such as topic evolution, group interaction, and public
emotion drifting, etc., usually incorporates complex correlation analysis from
the perspective of structure, group, and information. There is a need for the basic
theory and methods to support complex correlation, multi-dimensional, large-
scale, dynamic data.
6.3.4
Applications of Healthcare and Medical Big Data
Medical data is continuously and rapidly growing containing abundant and various
information values. Big data has unlimited potential for effectively storing, process-
ing, querying, and analyzing medical data. The application of medical big data will
profoundly influence the human health.
For example, Aetna Life Insurance Company selected 102 patients from a pool
of a 1,000 patients to complete an experiment in order to help predict the recovery
of patients with metabolic syndrome. In an independent experiment, it scanned
600,000 laboratory test results and 180,000 claims through a series of detection test
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