Mining User Generated Content (Hardcover)

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.

源自Facebook、LinkedIn、Twitter、Instagram、YouTube和許多其他社交網站的社交媒體，以及用戶共享的相關元數據，統稱為用戶生成內容（UGC）。為了分析UGC並獲取有關用戶行為的洞察，需要強大的技術來應對大量的實時、多媒體和多語言數據。研究人員還必須知道如何評估UGC的社交方面，例如用戶關係和有影響力的用戶。

《挖掘用戶生成內容》是第一個專注於彙編最新研究並探討UGC未來發展方向的努力。它解釋了如何收集、索引和分析UGC以揭示社交趨勢和用戶習慣。

本書分為四個部分，重點關注UGC的挖掘和應用。第一部分介紹了這個新興且令人興奮的主題。第二部分涵蓋了不同媒體類型的UGC挖掘，UGC的社交標註、社交網絡圖構建和社區挖掘，以及用於音樂檢索的UGC挖掘和難度較高的UGC情感分析。第三部分描述了各種類型的UGC的挖掘和搜索，包括知識提取、UGC內容的搜索技術，以及對日本博客的分析和標註的具體研究。應用方面的第四部分探討了使用UGC支持問答、信息摘要和推薦的方法。