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What is Social Analytics

Data-Driven Intelligent Business Sustainability
The application of data science technologies in social entities and social activities. Examples include web analysis, election analysis, and virtual network analysis.
Published in Chapter:
Meet Industry Needs in the Big Data Era: Data Science Curricula Development
Liguo Yu (Indiana University, South Bend, USA) and Yingmei Li (Harbin Normal University, China)
Copyright: © 2024 |Pages: 18
DOI: 10.4018/979-8-3693-0049-7.ch025
Abstract
The potential wide applications of big data analytics have created a high demand for data analysts in various industries, including business, healthcare, bioinformatics, politics, and management. As a result, higher education institutions are capitalizing on this opportunity by offering different data science programs to attract students and cater to industry needs. Over the past decade, there has been a rapid emergence of data science programs both nationally and globally. This chapter will begin by reviewing the impact of big data analytics on different industries. It will then proceed to describe various data science programs, including their curriculum design, course offerings, and target industry sectors for employment. Additionally, the chapter will address the weaknesses of some curricula and propose new teaching areas that are relevant to improve the learning outcomes of students. The aim of the suggestions is to better prepare data science students for the ever-evolving demands of big data analytics in the industry.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Social Media Mining
The extraction of valuable hidden insights from vast amounts of social media data to enable informed and insightful decision making.
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Competitive Analysis Based on Social Media Mining
The extraction of valuable hidden insights from vast amounts of social media data to enable informed and insightful decision making.
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