Big Data and Social Media Analytics : Trending Applications /

This edited book provides techniques which address various aspects of big data collection and analysis from social media platforms and beyond. It covers efficient compression of large networks, link prediction in hashtag graphs, visual exploration of social media data, identifying motifs in multivar...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Çakırtaş, Mehmet (Editor), Ozdemir, Mehmet Kemal (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Series:Lecture Notes in Social Networks,
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:This edited book provides techniques which address various aspects of big data collection and analysis from social media platforms and beyond. It covers efficient compression of large networks, link prediction in hashtag graphs, visual exploration of social media data, identifying motifs in multivariate data, social media surveillance to enhance search and rescue missions, recommenders for collaborative filtering and safe travel plans to high risk destinations, analysis of cyber influence campaigns on YouTube, impact of location on business rating, bibliographical and co-authorship network analysis, and blog data analytics. All these trending topics form a major part of the state of the art in social media and big data analytics. Thus, this edited book may be considered as a valuable source for readers interested in grasping some of the most recent advancements in this high trending domain.
Physical Description:1 online resource (VI, 245 pages 102 illustrations, 74 illustrations in color.)
ISBN:9783030670443
ISSN:2190-5436
DOI:10.1007/978-3-030-67044-3