From Social Data Mining and Analysis to Prediction and Community Detection

✍ Scribed by Mehmet Kaya, Özcan Erdoǧan, Jon Rokne (eds.)

• Publisher: Springer International Publishing
• Year: 2017
• Tongue: English
• Leaves: 248
• Series: Lecture Notes in Social Networks
• Edition: 1
• Category: Library

✦ Synopsis

This book presents the state-of-the-art in various aspects of analysis and mining of online social networks. Within the broader context of online social networks, it focuses on important and upcoming topics of social network analysis and mining such as the latest in sentiment trends research and a variety of techniques for community detection and analysis. The book collects chapters that are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2015), which was held in Paris, France in August 2015. All papers have been peer reviewed and checked carefully for overlap with the literature. The book will appeal to students and researchers in social network analysis/mining and machine learning.

✦ Table of Contents

Front Matter....Pages i-x
An Offline–Online Visual Framework for Clustering Memes in Social Media....Pages 1-29
A System for Email Recipient Prediction....Pages 31-59
A Credibility Assessment Model for Online Social Network Content....Pages 61-77
Web Search Engine-Based Representation for Arabic Tweets Categorization....Pages 79-101
Sentiment Trends and Classifying Stocks Using P-Trees....Pages 103-121
Mining Community Structure with Node Embeddings....Pages 123-140
A LexDFS-Based Approach on Finding Compact Communities....Pages 141-177
Computational Data Sciences and the Regulation of Banking and Financial Services....Pages 179-209
Frequent and Non-frequent Sequential Itemsets Detection....Pages 211-238
Back Matter....Pages 239-245

✦ Subjects

Data Mining and Knowledge Discovery;Artificial Intelligence (incl. Robotics);Applications of Graph Theory and Complex Networks