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Erschienen in: The VLDB Journal 1/2020

18.09.2019 | Special Issue Paper

Microblogs data management: a survey

verfasst von: Amr Magdy, Laila Abdelhafeez, Yunfan Kang, Eric Ong, Mohamed F. Mokbel

Erschienen in: The VLDB Journal | Ausgabe 1/2020

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Abstract

Microblogs data is the microlength user-generated data that is posted on the web, e.g., tweets, online reviews, comments on news and social media. It has gained considerable attention in recent years due to its widespread popularity, rich content, and value in several societal applications. Nowadays, microblogs applications span a wide spectrum of interests including targeted advertising, market reports, news delivery, political campaigns, rescue services, and public health. Consequently, major research efforts have been spent to manage, analyze, and visualize microblogs to support different applications. This paper gives a comprehensive review of major research and system work in microblogs data management. The paper reviews core components that enable large-scale querying and indexing for microblogs data. A dedicated part gives particular focus for discussing system-level issues and on-going effort on supporting microblogs through the rising wave of big data systems. In addition, we review the major research topics that exploit these core data management components to provide innovative and effective analysis and visualization for microblogs, such as event detection, recommendations, automatic geotagging, and user queries. Throughout the different parts, we highlight the challenges, innovations, and future opportunities in microblogs data research.

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Metadaten
Titel
Microblogs data management: a survey
verfasst von
Amr Magdy
Laila Abdelhafeez
Yunfan Kang
Eric Ong
Mohamed F. Mokbel
Publikationsdatum
18.09.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
The VLDB Journal / Ausgabe 1/2020
Print ISSN: 1066-8888
Elektronische ISSN: 0949-877X
DOI
https://doi.org/10.1007/s00778-019-00569-6

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