Big Data Research for Social Sciences and Social Impact

A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges....

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Bibliographic Details
Main Author: Visvizi, Anna
Other Authors: Lytras, Miltiadis, Chui, Kwok Tai
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:
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Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers-A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization's Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context-Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/
Physical Description:1 electronic resource (416 p.)
ISBN:9783039282203
9783039282210
books978-3-03928-221-0