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Social Network Based Big Data Analysis and Applications

Overview of attention for book
Cover of 'Social Network Based Big Data Analysis and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Twitter as a Source for Time- and Domain-Dependent Sentiment Lexicons
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    Chapter 2 Hiding in Plain Sight: The Anatomy of Malicious Pages on Facebook
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    Chapter 3 Extraction and Analysis of Dynamic Conversational Networks from TV Series
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    Chapter 4 Diversity and Influence as Key Measures to Assess Candidates for Hiring or Promotion in Academia
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    Chapter 5 Timelines of Prostate Cancer Biomarkers
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    Chapter 6 Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks
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    Chapter 7 Influence and Extension of the Spiral of Silence in Social Networks: A Data-Driven Approach
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    Chapter 8 Prepaid or Postpaid? That Is the Question: Novel Methods of Subscription Type Prediction in Mobile Phone Services
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    Chapter 9 Dynamic Pattern Detection for Big Data Stream Analytics
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    Chapter 10 Community-Based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation
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    Chapter 11 Combining Feature Extraction and Clustering for Better Face Recognition
Attention for Chapter 10: Community-Based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation
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Citations

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Summary Dimensions citations
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Chapter title
Community-Based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation
Chapter number 10
Book title
Social Network Based Big Data Analysis and Applications
Published by
Springer, Cham, January 2018
DOI 10.1007/978-3-319-78196-9_10
Book ISBNs
978-3-31-978195-2, 978-3-31-978196-9
Authors

Mo Yu, Xiaolong (Luke) Zhang, Dongwon Lee, Derek Kreager

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Other 2 25%
Student > Master 2 25%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 4 50%
Social Sciences 2 25%
Unknown 2 25%

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