Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information.
Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.
The many academic areas covered in this publication include, but are not limited to:
- Content Specific Modeling
- Distributed Memory
- Graph Mining
- Influence Maximization
- Information Spread Control
- Link Prediction
- Probabilistic Exploration
- ISBN13 9781522528142
- Publish Date 30 July 2017 (first published 13 July 2017)
- Publish Status Active
- Publish Country US
- Imprint IGI Global
- Format Hardcover
- Pages 355
- Language English