02639oam 2200625I 450 991078912300332120170817193549.00-429-08761-61-4665-5741-910.1201/b16413 (CKB)3710000000083489(EBL)1460735(SSID)ssj0001112686(PQKBManifestationID)11615185(PQKBTitleCode)TC0001112686(PQKBWorkID)11161391(PQKB)11177035(MiAaPQ)EBC1460735(OCoLC)868487901(CaSebORM)9781466557413(EXLCZ)99371000000008348920180331h20142014 uy 0engur|n|---|||||txtccrMining user generated content /edited by Marie-Francine Moens, Katholieke Universiteit Leuven, Belgium, Juanzi Li, Tsinghua University, China, Tat-Seng Chua, National University of Singapore, Singapore1st editionBoca Raton :Taylor & Francis,[2014]©20141 online resource (446 p.)Chapman & Hall/CRC social media and social computing seriesA Chapman and Hall book.1-4665-5740-0 Includes bibliographical references.part I. Introduction -- part II. Mining different media -- part III. Mining and searching different types of UGC -- part IV. Applications.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 Social Media and Social ComputingData miningUser-generated contentData mining.User-generated content.006.3/12006.312COM021000COM021030COM079010bisacshMoens Marie-Francine1957-Li JuanziChua Tat-SengFlBoTFGFlBoTFGBOOK9910789123003321Mining user generated content3810675UNINA