474 Pages 47 B/W Illustrations
    by Chapman & Hall

    Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other networking sites, the social media shared by users and the associated metadata are collectively known as user generated content (UGC). To analyze UGC and glean insight about user behavior, robust techniques are needed to tackle the huge amount of real-time, multimedia, and multilingual data. Researchers must also know how to assess the social aspects of UGC, such as user relations and influential users.

    Mining User Generated Content is the first focused effort to compile state-of-the-art research and address future directions of UGC. It explains how to collect, index, and analyze UGC to uncover social trends and user habits.

    Divided into four parts, the book focuses on the mining and applications of UGC. The first part presents an introduction to this new and exciting topic. Covering the mining of UGC of different medium types, the second part discusses the social annotation of UGC, social network graph construction and community mining, mining of UGC to assist in music retrieval, and the popular but difficult topic of UGC sentiment analysis. The third part describes the mining and searching of various types of UGC, including knowledge extraction, search techniques for UGC content, and a specific study on the analysis and annotation of Japanese blogs. The fourth part on applications explores the use of UGC to support question-answering, information summarization, and recommendations.

    Mining of User Generated Content and Its Applications Marie-Francine Moens, Juanzi Li, and Tat-Seng Chua
    The Web and Web Trends
    Defining User Generated Content
    A Brief History of Creating, Searching and Mining User Generated Content
    Goals of the Book
    User Generated Content: Concepts and Bottlenecks
    Organization of the Book
    Mining User Generated Content: Broader Context

    Mining Different Media
    Social Annotation Jia Chen, Shenghua Bao, Haofen Wang, and Yong Yu
    Research on Social Annotations
    Techniques in Social Annotations
    Application of Social Annotations

    Sentiment Analysis in UGC Ning Yu
    Major Issues in Sentiment Analysis

    Mining User Generated Data for Music Information Retrieval Markus Schedl, Mohamed Sordo, Noam Koenigstein, and Udi Weinsberg
    Introduction to Music Information Retrieval
    Web Pages
    Explicit User Ratings
    Peer-to-Peer Networks
    Social Tags
    Social Networks

    Graph and Network Pattern Mining Jan Ramon, Constantin Comendant, Mostafa Haghir Chehreghani, and Yuyi Wang
    Basic Concepts
    Transactional Graph Pattern Mining
    Single Network Mining
    Concluding Remarks
    Additional Reading

    Mining and Searching Different Types of UGC
    Knowledge Extraction from Wiki/BBS/Blogs/News Websites Jun Zhao, Kang Liu, Guangyou Zhou, Xianpei Han, Zhenyu Qi, and Yang Liu
    Entity Recognition and Expansion
    Relation Extraction
    Named Entity Disambiguation

    User Generated Content Search Roi Blanco, Manuel Eduardo Ares Brea, and Christina Lioma
    Overview of State of the Art
    Social Tags for Query Expansion

    Annotating Japanese Blogs with Syntactic and Affective Information Michal Ptaszynski, Yoshio Momouchi, Jacek Maciejewski, Pawel Dybala, Rafal Rzepka, and Kenji Araki
    Related Research
    YACIS Corpus Compilation
    YACIS Corpus Annotation
    Conclusions and Future Work

    Question Answering of UGC Chin-Yew Lin
    Question Answering by Searching Questions?
    Question Search
    Question Quality, Answer Quality, and User Expertise

    Summarization of UGC Dominic Rout and Kalina Bontcheva
    Automatic Text Summarization: A Brief Overview
    Why Is User Generated Content a Challenge?
    Text Summarization of UGC
    Structured, Sentiment-Based Summarization of UGC
    Keyword-based Summarization of UGC
    Visual Summarization of UGC
    Evaluating UGC Summaries
    Outstanding Challenges

    Recommender Systems Claudio Lucchese, Cristina Ioana Muntean, Raffaele Perego, and Fabrizio Silvestri
    Recommendation Techniques
    Exploiting Query Logs for Recommending Related Queries
    Exploiting Photo Sharing and Wikipedia for Touristic Recommendations
    Exploiting Twitter and Wikipedia for News Recommendation
    Recommender Systems for Tags

    Conclusions and a Roadmap for Future Developments Marie-Francine Moens, Juanzi Li, and Tat-Seng Chua
    Summary of the Main Findings



    Marie-Francine Moens, Juanzi Li, Tat-Seng Chua

    "This book is timely in collating the experiences and progress in the user-generated content (UGC) area. … this book is contemporary and provides insights into the UGC work in a comprehensible way. It will be well appreciated by researchers, academicians, and practitioners."
    Computing Reviews, June 2015