Social Network Analysis in Telecommunications

Foreword.

Preface.

Acknowledgments.

Part I: Foundation of Social Network Analysis.

Chapter 1: An Introduction to Social Network Analysis.

Evolution of Social Network Analysis.

Actor and Relations Building Social Networks.

Influence.

Structures of Social Networks.

Analyses of Social Networks.

Graph Theory.

A Note on Statistics and Social Network Data.

Summary.

Chapter 2: Formal Methods for Network Analysis.

A Graphical Approach.

Levels of Measurement

Summary.

Chapter 3: Theoretical Foundation.

Data for Social Network Analysis.

Identifying Populations, Samples, and Boundaries.

Modality and Levels of Analysis.

Correlating Nodes into the Network.

Scales of Measurement.

Summary.

Chapter 4: Measures of Power and Influence.

Types of Networks.

Degree Centrality.

Closeness Centrality.

Betweenness Centrality.

Freeman’s Approach to Binary Relations.

Summary.

Part II: Social Network Analysis Case Study.

Chapter 5: Telecommunications Environment.

New Challenges in Telecommunications Market.

Social Networks in Telecommunications' Environment.

Traditional Predictive Models Based on Artificial Neural Networks.

Combined Modeling Approach.

Feasible Action Plan Based on the Combined Approach.

Benefits from the Combined Modeling Approach.

Summary.

Chapter 6: Social Network Modeling.

Customer Influence Factor Modeling.

The Data Extraction Process for Social Network Analysis Modeling.

The Data Preparation Process for Social Network Analysis Modeling.

Computing the Basic Social Network Measures.

Computing the Customer Influence Factor.

Adjusting the Influence Factor According to the Past Events.

Summary.

Chapter 7: Assessing the Social Network Model.

Assessing the Customer Influence Factor Due to the Business Events.

Plotting the Social Network.

Establishing the Distance for the Customers Based on Similarity.

Summary.

Chapter 8: Evaluating the Business Results.

Correlation between the Customer Influence and the Past Events of Churn.

Correlation between the Customer Influence and the Past Events of Bundle Diffusion.

The Social Network’s Evolution in a Chain Process Perspective Considering. Business Events.

The Bundle Diffusion Process Analyzed over Time.

Enhanced Data Analysis Visualization.

Geographical Visualization Analysis.

Summary.

Chapter 9: Final Remarks for the Case Study.

Products and Service Choice.

Further Inferences and Future Works.

Summary.

Part III: SAS Capabilities for Social Network Analysis.

Chapter 10: Basic Statistics.

Descriptive Analysis.

Univariate Analysis.

Grouping Based on Relationship Similarities.

Summary.

Chapter 11: Overview of the Link Analysis Node.

Centrality Measures.

Result Analysis.

Summary.

Chapter 12: Visualization Capabilities for Social Network Analysis.

Network Visualization Workshop.

%DS2CONST Macro.

%DMLINKVW Macro.

Summary.

Chapter 13: A Note about OPTGRAPH.

Recognizing Groups inside Network.

Individual Measures for the Network.

Summary.

Bibliography.

About the Author.

Index.

CARLOS ANDRE REIS PINHEIRO has conducted over the last two years postdoctoral research in social network analysis at the School of Computing, Dublin City University (DCU), Ireland. He holds a doctoral degree in computer science from Federal University of Rio de Janeiro, Brazil. Before joining DCU, he did postdoctoral research in optimization at Instituto Nacional de Matemática Pura e Aplicada (IMPA) in Brazil, one of the most prestigious mathematical institutes in the world. He has been with Oi, the largest telecommunications company in Brazil, since 2000. He has published several papers in international journals and has also written four books that focus on the Internet, database, Web warehousing, and analytical intelligence.