Social Big Data Analytics

This 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 ...

Social Big Data Analytics

This 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 analyse 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, scrutinise 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 visualisation tools in accessible an attractive display.

More Books:

Social Big Data Analytics
Language: en
Pages: 218
Authors: Bilal Abu-Salih, Pornpit Wongthongtham, Dengya Zhu, Kit Yan Chan, Amit Rudra
Categories: Business & Economics
Type: BOOK - Published: 2021-03-10 - Publisher: Springer Nature

This 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
ECSM 2017 4th European Conference on Social Media
Language: en
Pages:
Authors: Academic Conferences and Publishing Limited
Categories: Business & Economics
Type: BOOK - Published: 2017-07-03 - Publisher: Academic Conferences and publishing limited

Books about ECSM 2017 4th European Conference on Social Media
People Analytics in the Era of Big Data
Language: en
Pages: 416
Authors: Jean Paul Isson, Jesse S. Harriott
Categories: Business & Economics
Type: BOOK - Published: 2016-04-25 - Publisher: John Wiley & Sons

Apply predictive analytics throughout all stages of workforce management People Analytics in the Era of Big Data provides a blueprint for leveraging your talent pool through the use of data analytics. Written by the Global Vice President of Business Intelligence and Predictive Analytics at Monster Worldwide, this book is packed
Classification, (Big) Data Analysis and Statistical Learning
Language: en
Pages: 242
Authors: Francesco Mola, Claudio Conversano, Maurizio Vichi
Categories: Mathematics
Type: BOOK - Published: 2018-02-21 - Publisher: Springer

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well
Data Mining Approaches for Big Data and Sentiment Analysis in Social Media
Language: en
Pages: 313
Authors: Gupta, Brij B., Perakovi?, Dragan, Abd El-Latif, Ahmed A., Gupta, Deepak
Categories: Computers
Type: BOOK - Published: 2021-12-31 - Publisher: IGI Global

Social media sites are constantly evolving with huge amounts of scattered data or big data, which makes it difficult for researchers to trace the information flow. It is a daunting task to extract a useful piece of information from the vast unstructured big data; the disorganized structure of social media