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Big Data and Social Media Analytics ...
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SpringerLink (Online service)
Big Data and Social Media Analytics = Trending Applications /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Big Data and Social Media Analytics/ edited by Mehmet Çakırtaş, Mehmet Kemal Ozdemir.
Reminder of title:
Trending Applications /
other author:
Çakırtaş, Mehmet.
Description:
VI, 245 p. 102 illus., 74 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Statistics . -
Online resource:
https://doi.org/10.1007/978-3-030-67044-3
ISBN:
9783030670443
Big Data and Social Media Analytics = Trending Applications /
Big Data and Social Media Analytics
Trending Applications /[electronic resource] :edited by Mehmet Çakırtaş, Mehmet Kemal Ozdemir. - 1st ed. 2021. - VI, 245 p. 102 illus., 74 illus. in color.online resource. - Lecture Notes in Social Networks,2190-5436. - Lecture Notes in Social Networks,.
Chapter 1. Twenty Years of Network Science: A Bibliographic and Co-Authorship Network Analysis -- Chapter 2. Impact of Locational Factors on Business Ratings/Reviews: A Yelp and TripAdvisor Study -- Chapter 3. Identifying Reliable Recommenders in Users’ Collaborating Filtering and Social Neighbourhoods -- Chapter 4. Safe Travelling Period Recommendation to High Attack Risk European Destinations based on Past Attack Information -- Chapter 5. Analyzing Cyber Influence Campaigns on YouTube using YouTubeTracker -- Chapter 6. Blog Data Analytics Using Blogtrackers -- Chapter 7. Using Social Media Surveillance in order to Enhance the Effectiveness of Crew Members in Search and Rescue Missions -- Chapter 8. Visual Exploration and Debugging of Machine Learning Classification over Social Media Data -- Chapter 9. Efficient and Flexible Compression of Very Sparse Networks of Big Data -- Chapter 10. Weather Big Data Analytics: Seeking Motifs in Multivariate Weather Data -- Chapter 11. Analysis of Link Prediction Algorithms in Hashtag Graphs.
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.
ISBN: 9783030670443
Standard No.: 10.1007/978-3-030-67044-3doiSubjects--Topical Terms:
1253516
Statistics .
LC Class. No.: QA276-280
Dewey Class. No.: 519.5
Big Data and Social Media Analytics = Trending Applications /
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Chapter 1. Twenty Years of Network Science: A Bibliographic and Co-Authorship Network Analysis -- Chapter 2. Impact of Locational Factors on Business Ratings/Reviews: A Yelp and TripAdvisor Study -- Chapter 3. Identifying Reliable Recommenders in Users’ Collaborating Filtering and Social Neighbourhoods -- Chapter 4. Safe Travelling Period Recommendation to High Attack Risk European Destinations based on Past Attack Information -- Chapter 5. Analyzing Cyber Influence Campaigns on YouTube using YouTubeTracker -- Chapter 6. Blog Data Analytics Using Blogtrackers -- Chapter 7. Using Social Media Surveillance in order to Enhance the Effectiveness of Crew Members in Search and Rescue Missions -- Chapter 8. Visual Exploration and Debugging of Machine Learning Classification over Social Media Data -- Chapter 9. Efficient and Flexible Compression of Very Sparse Networks of Big Data -- Chapter 10. Weather Big Data Analytics: Seeking Motifs in Multivariate Weather Data -- Chapter 11. Analysis of Link Prediction Algorithms in Hashtag Graphs.
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