國立虎尾科技大學 |

Social network based big data analysis and applications

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Social network based big data analysis and applications/ edited by Mehmet Kaya ... [et al.].
other author:	Kaya, Mehmet.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	x, 249 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Online social networks. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-78196-9
ISBN:	9783319781969

Social network based big data analysis and applications
Social network based big data analysis and applications[electronic resource] /edited by Mehmet Kaya ... [et al.]. - Cham :Springer International Publishing :2018. - x, 249 p. :ill., digital ;24 cm. - Lecture notes in social networks,2190-5428. - Lecture notes in social networks..

Chapter1. Twitter as a Source for Time and Domain Dependent Sentiment Lexicons -- Chapter2. Hiding in Plain Sight: The Anatomy of Malicious Pages on Facebook -- Chapter3. Extraction and Analysis of Dynamic Conversational Networks from TV Series -- Chapter4. Diversity and Influence as Key Measures to Assess Candidates for Hiring or Promotion in Academia -- Chapter5. Timelines of Prostate Cancer Biomarkers -- Chapter6. Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks -- Chapter7. Influence and Extension of the Spiral of Silence in Social Networks: A Data-driven Approach -- Chapter8. Prepaid or Postpaid? That is the question.\\ Novel Methods of Subscription Type Prediction in Mobile Phone Services -- Chapter9. Dynamic Pattern Detection for Big Data Stream Analytics -- Chapter10. Community-based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation -- Chapter11. Combining Feature Extraction and Clustering for Better Face Recognition.

This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.

ISBN: 9783319781969

Standard No.: 10.1007/978-3-319-78196-9doiSubjects--Topical Terms:

565357
Online social networks.

LC Class. No.: HM742 / .S635 2018

Dewey Class. No.: 302.30285

Social network based big data analysis and applications
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505 0 $a Chapter1. Twitter as a Source for Time and Domain Dependent Sentiment Lexicons -- Chapter2. Hiding in Plain Sight: The Anatomy of Malicious Pages on Facebook -- Chapter3. Extraction and Analysis of Dynamic Conversational Networks from TV Series -- Chapter4. Diversity and Influence as Key Measures to Assess Candidates for Hiring or Promotion in Academia -- Chapter5. Timelines of Prostate Cancer Biomarkers -- Chapter6. Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks -- Chapter7. Influence and Extension of the Spiral of Silence in Social Networks: A Data-driven Approach -- Chapter8. Prepaid or Postpaid? That is the question.\\ Novel Methods of Subscription Type Prediction in Mobile Phone Services -- Chapter9. Dynamic Pattern Detection for Big Data Stream Analytics -- Chapter10. Community-based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation -- Chapter11. Combining Feature Extraction and Clustering for Better Face Recognition.
520 $a This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
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