Mining User Generated Content

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.

Introduction Mining of User Generated Content and Its Applications Marie-Francine Moens, Juanzi Li, and Tat-Seng ChuaThe Web and Web TrendsDefining 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 YuResearch on Social Annotations Techniques in Social AnnotationsApplication of Social Annotations Sentiment Analysis in UGC Ning YuIntroduction BackgroundMajor Issues in Sentiment Analysis Mining User Generated Data for Music Information Retrieval Markus Schedl, Mohamed Sordo, Noam Koenigstein, and Udi WeinsbergIntroduction to Music Information RetrievalWeb Pages Microblogs Explicit User Ratings Peer-to-Peer Networks Social Tags Social Networks Conclusions Graph and Network Pattern Mining Jan Ramon, Constantin Comendant, Mostafa Haghir Chehreghani, and Yuyi WangIntroduction Basic Concepts Transactional Graph Pattern MiningSingle Network MiningConcluding Remarks Additional Reading Glossary 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 LiuIntroductionEntity Recognition and ExpansionRelation ExtractionNamed Entity DisambiguationConclusion User Generated Content Search Roi Blanco, Manuel Eduardo Ares Brea, and Christina LiomaIntroduction Overview of State of the ArtSocial Tags for Query ExpansionConclusions Annotating Japanese Blogs with Syntactic and Affective Information Michal Ptaszynski, Yoshio Momouchi, Jacek Maciejewski, Pawel Dybala, Rafal Rzepka, and Kenji ArakiIntroduction Related Research YACIS Corpus Compilation YACIS Corpus Annotation Applications Discussion Conclusions and Future Work Applications Question Answering of UGC Chin-Yew LinIntroduction Question Answering by Searching Questions? Question SearchQuestion Quality, Answer Quality, and User ExpertiseSummary Summarization of UGC Dominic Rout and Kalina BontchevaIntroduction 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 Summary Recommender Systems Claudio Lucchese, Cristina Ioana Muntean, Raffaele Perego, and Fabrizio SilvestriRecommendation TechniquesExploiting Query Logs for Recommending Related Queries Exploiting Photo Sharing and Wikipedia for Touristic RecommendationsExploiting Twitter and Wikipedia for News Recommendation Recommender Systems for TagsConclusions Conclusions and a Roadmap for Future Developments Marie-Francine Moens, Juanzi Li, and Tat-Seng ChuaSummary of the Main Findings Roadmap Bibliography