000			02909nam a22002537a 4500
999			_c4133 _d4133
005			20221201112427.0
008			221201b ||||| |||| 00| 0 eng d
020			_a9789813366510
082			_a005.7 _bABU
100			_aAbu-Salih, Bilal _99333
245			_aSocial big data analytics: _bpractices, techniques, and applications
260			_bSpringer _aSwitzerland _c2021
300			_ax, 218 p.
365			_aEURO _b129.99
520			_aThis book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyze the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinize the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualization tools in accessible an attractive display.
650			_aBig data _9212
650			_aMachine learning _92343
650			_aMarketing research _9276
650			_aInternet marketing _9786
700			_aWongthongtham, Pornpit _910402
700			_aChan, Kit Yan _910403
700			_aRudra, Amit _910404
942			_2ddc _cBK