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A Systematic Review Towards Big Data Analytics in Social Media
The recent advancement in internet 2.0 creates a scope to connect people worldwide using society 2.0 and web 2.0 technologies. This new era allows the consumer to directly connect with other individuals, business corporations, and the government. People are open to sharing opinions, views, and ideas on any topic in different formats out loud. This creates the opportunity to make the \"Big Social Data\" handy by implementing machine learning approaches and social data analytics. This study offers an overview of recent works in social media, data science, and machine learning to gain a wide perspective on social media big data analytics. We explain why social media data are significant elements of the improved data-driven decision-making process. We propose and build the \"Sunflower Model of Big Data\" to define big data and bring it up to date with technology by combining 5 V’s and 10 Bigs. We discover the top ten social data analytics to work in the domain of social media platforms. A comprehensive list of relevant statistical/machine learning methods to implement each of these big data analytics is discussed in this work. \"Text Analytics\" is the most used analytics in social data analysis to date. We create a taxonomy on social media analytics to meet the need and provide a clear understanding. Tools, techniques, and supporting data type are also discussed in this research work. As a result, researchers will have an easier time deciding which social data analytics would best suit their needs.
Journal Article
New Complex Analytic Methods in the Study of Non-Orientable Minimal Surfaces in ℝⁿ
The aim of this work is to adapt the complex analytic methods originating in modern Oka theory to the study of non-orientable
conformal minimal surfaces in
All our new tools mentioned above apply to non-orientable minimal surfaces endowed with a fixed choice
of a conformal structure. This enables us to obtain significant new applications to the global theory of non-orientable minimal
surfaces. In particular, we construct proper non-orientable conformal minimal surfaces in
eBook
Data visualization : a practical introduction
\"This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data visualization builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language ....\"--Page 4 of cover.
Book
Business Intelligence and Analytics: From Big Data to Big Impact
Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifles the evolution, applications, and emerging research areas of BI&A. BI& A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework.
Journal Article
The age of prediction : algorithms, AI, and the shifting shadows of risk
\"The interplay between prediction and risk and role of advanced predictive technologies (biotechnology, AI, and big data) in provoking social change\"-- Provided by publisher.
BOOK
Tackling the HR digitalization challenge: key factors and barriers to HR analytics adoption
Purpose
This paper aims to contribute to the literature on human resources (HR) digitalization, specifically on HR analytics, disentangling the concept of analytics applied to HR and explaining the factors that hinder companies from moving to analytics. Therefore, the central research questions addressed in this study are: what does HR analytics encompass? What impedes the adoption of analytics in HR within organizations?
Design/methodology/approach
The authors performed a comprehensive literature review on analytics as applied in HR. The authors relied on two of the major multidisciplinary publication databases (i.e. Scopus and WoS). A total of 64 manuscripts from 2010 to 2019 were content analyzed.
Findings
The results reveal that there is an ongoing confusion on HR analytics conceptualization. Yet, it seems that there is an emerging consensus on what HR analytics encompasses. The authors have identified 14 different barriers for HR analytics adoption grouped into four categories, namely, data and models, software and technology, people and management. Grounding on them the authors propose a set of 14 key factors to help to successfully adopt HR Analytics in companies.
Originality/value
This paper brings clarity over the conceptualization of HR analytics by offering a comprehensive definition. Additionally, it facilitates business and HR leaders in making informed decisions on adopting and implementing HR analytics. Moreover, it assists HR researchers in positioning their paper more explicitly in current debates and encouraging them to develop some future avenues of research departing from some questions posed.
Journal Article
Local dynamics of non-invertible maps near normal surface singularities
We study the problem of finding algebraically stable models for non-invertible holomorphic fixed point germs
eBook