Data Mining for Social Network Data

Driven by counter-terrorism efforts, marketing analysis, and the explosion in on-line social networking, data mining has moved to the top of the agenda in information science. This book presents a broad range of recent studies in social networking analysis.

Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, activities in open for a and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution pattern discovery using machine learning approaches and multi-agent based simulations. Editors are three rising stars in world of data mining, knowledge discovery, social network analysis, and information infrastructures, and are anchored by Springer author/editor Hsinchun Chen (Terrorism Informatics; Medical Informatics; Digital Government), who is one of the most prominent intelligence analysis and data mining experts in the world.

Using machine learning techniques to analyze social networks A multidisciplinary source, which will draw the interest of researchers and students in sociology, computer science and statistics The research outcome will be of value to study different problems of social impact including market analysis, terrorist groups, etc. Includes supplementary material: sn.pub/extras

Texte du rabat
Social Network Data Mining: Research Questions, Techniques, and Applications Nasrullah Memon, Jennifer Xu, David L. Hicks and Hsinchun Chen Automatic expansion of a social network using sentiment analysis Hristo Tanev, Bruno Pouliquen, Vanni Zavarella and Ralf Steinberger Automatic mapping of social networks of actors from text corpora: Time series analysis James A. Danowski and Noah Cepela A social network based recommender system (SNRS) Jianming He and Wesley W. Chu Network analysis of U.S. air transportation network Guangying Hua, Yingjie Sun, and Dominique Haughton Identifying high-status nodes in knowledge networks Siddharth Kaza and Hsinchun Chen Modularity for bipartite networks Tsuyoshi Murata ONDOCS: Ordering nodes to detect overlapping community structure Jiyang Chen, Osmar R. Zaiane, J¨org Sander, and Randy Goebel Framework for Fast Identification of Community Structures in Large-Scale Social Networks Yutaka I. Leon-Suematsu and Kikuo Yuta Geographically organized small communities and the hardness of clustering social networks Miklós Kurucz and András A. Benczúr Integrating genetic algorithms and fuzzy logic for web structure optimization Iltae Lee, Negar Koochakzadeh, Keivan Kianmehr, Reda Alhajj, and Jon Rokne

Contenu
Social Network Data Mining: Research Questions, Techniques, and Applications.- Automatic Expansion of a Social Network Using Sentiment Analysis.- Automatic Mapping of Social Networks of Actors from Text Corpora: Time Series Analysis.- A Social Network-Based Recommender System (SNRS).- Network Analysis of US Air Transportation Network.- Identifying High-Status Nodes in Knowledge Networks.- Modularity for Bipartite Networks.- ONDOCS: Ordering Nodes to Detect Overlapping Community Structure.- Framework for Fast Identification of Community Structures in Large-Scale Social Networks.- Geographically Organized Small Communities and the Hardness of Clustering Social Networks.- Integrating Genetic Algorithms and Fuzzy Logic for Web Structure Optimization.