A framework for social media data analytics using Elasticsearch and Kibana

被引:0
作者
Neel Shah
Darryl Willick
Vijay Mago
机构
[1] Lakehead University,Deparment of Computer Science
来源
Wireless Networks | 2022年 / 28卷
关键词
Social media; Big data; Real-time analysis; Elasticsearch; Visualization;
D O I
暂无
中图分类号
学科分类号
摘要
Real-time online data processing is quickly becoming an essential tool in the analysis of social media for political trends, advertising, public health awareness programs and policy making. Traditionally, processes associated with offline analysis are productive and efficient only when the data collection is a one-time process. Currently, cutting edge research requires real-time data analysis that comes with a set of challenges, particularly the efficiency of continuous data fetching within the context of present NoSQL and relational databases. In this paper, we demonstrate a solution to effectively adsress the challenges of real-time analysis using a configurable Elasticsearch search engine. We are using a distributed database architecture, pre-build indexing and standardizing the Elasticsearch framework for large scale text mining. The results from the query engine are visulized in almost real-time.
引用
收藏
页码:1179 / 1187
页数:8
相关论文
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