<p><p></p><p></p><p>This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power of big data processing to graph data. Designed as a step-by-step self-study guide for everyone interested in large-scale graph processing, it
Graph Theoretic Approaches for Analyzing Large-Scale Social Networks
✍ Scribed by Natarajan Meghanathan (editor)
- Publisher
- Information Science Reference
- Year
- 2017
- Tongue
- English
- Leaves
- 377
- Series
- Advances in Wireless Technologies and Telecommunication (AWTT)
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
This book brings together the recent research advances in the field of graph theory for analyzing large-scale social networks. It brings together the research advances in state-of-the-art graph theory algorithms and techniques that have contributed to the effective analysis of social networks, especially those networks that generate significant amount of data and involve several thousands of users.
✦ Table of Contents
Table of Contents
Preface
1 A Walk Through Social Network Analysis: Opportunities, Limitations, and Threats • Atul Srivastava, Anuradha Pillai, Dimple Juneja Gupta
2 Graph Tools for Social Network Analysis • Nadeem Akhtar, Mohd Vasim Ahamad
3 An Approach to Mining Information From Telephone Graph Using Graph Mining Techniques • Bapuji Rao, Sasmita Mishra, Sarojananda Mishra
4 A Dynamic and Context-Aware Social Network Approach for Multiple Criteria Decision Making Through a Graph-Based Knowledge Learning • Alessandro Di Stefano, Marialisa Scatà, Aurelio La Corte, Evelina Giacchi
5 Undirected Bipartite Networks as an Alternative Methodology to Probabilistic Exploration: Online Interaction and Academic Attainment in MOOC • Juan-Francisco Martínez-Cerdá, Joan Torrent-Sellens
6 Social Network Analysis of Different Parameters Derived From Real-Time Facebook Profiles • Paramita Dey, Krishnendu Dutta
7 Context Specific Modeling of Communicational and Informational Content in Facebook • Johannes Schick, Martin Kuboschek, Wolfram Manfred Lippe
8 Hadoop-Based Distributed K-Shell Decomposition for Social Networks • Katerina Pechlivanidou, Dimitrios Katsaros, Leandros Tassiulas
9 Parallelizing Large-Scale Graph Algorithms Using the Apache Spark-Distributed Memory System • Ahmad Askarian, Rupei Xu, Andras Farago
10 Link Prediction in Social Networks • Sovan Samanta, Madhumangal Pal
11 Visualizing Co-Authorship Social Networks and Collaboration Recommendations With CNARe • Michele A. Brandão, Matheus A. Diniz, Guilherme A. de Sousa, Mirella M. Moro
12 Community Detection in Large-Scale Social Networks: A Survey • S Rao Chintalapudi, M. H. M. Krishna Prasad
13 Spreading Activation Connectivity Based Approach to Network Clustering • Alexander Troussov, Sergey Maruev, Sergey Vinogradov, Mikhail Zhizhin
14 Scalable Method for Information Spread Control in Social Networks • Michal Wojtasiewicz, Mieczysław Kłopotek
15 The Eternal-Return Model of Human Mobility and Its Impact on Information Flow • Martine Collard, Philippe Collard, Erick Stattner
16 Towards a Unified Semantic Model for Online Social Networks to Ensure Interoperability and Aggregation for Analysis • Asmae El Kassiri, Fatima-Zahra Belouadha
17 Can We Trust the Health Information We Find Online? Identification of Influential Nodes • Leila Weitzel, Paulo Quaresma, Jose Palazzo Moreira de Oliveira, Danilo Artigas
Compilation of References
About the Contributors
Index
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