Twitter analytics: a big data management perspective

Oshini Goonetilleke, T. Sellis, Xiuzhen Zhang, Saket K. Sathe
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引用次数: 46

Abstract

With the inception of the Twitter microblogging platform in 2006, a myriad of research efforts have emerged studying different aspects of the Twittersphere. Each study exploits its own tools and mechanisms to capture, store, query and analyze Twitter data. Inevitably, platforms have been developed to replace this ad-hoc exploration with a more structured and methodological form of analysis. Another body of literature focuses on developing languages for querying Tweets. This paper addresses issues around the big data nature of Twitter and emphasizes the need for new data management and query language frameworks that address limitations of existing systems. We review existing approaches that were developed to facilitate twitter analytics followed by a discussion on research issues and technical challenges in developing integrated solutions.
Twitter分析:大数据管理视角
随着Twitter微博平台在2006年的诞生,无数的研究努力已经出现,研究Twitter圈的不同方面。每项研究都利用自己的工具和机制来获取、存储、查询和分析Twitter数据。不可避免地,平台已经被开发出来,用更结构化和方法论的分析形式取代这种特殊的探索。另一个文献集中于开发查询tweet的语言。本文讨论了围绕Twitter大数据特性的问题,并强调需要新的数据管理和查询语言框架来解决现有系统的局限性。我们回顾了为促进twitter分析而开发的现有方法,然后讨论了开发集成解决方案的研究问题和技术挑战。
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