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:
Kde
Gwr
Sde
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
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245 0 0 |a Big Data Research for Social Sciences and Social Impact  |h Elektronische Ressource 
260 |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2020 
300 |a 1 electronic resource (416 p.) 
653 |a machine learning 
653 |a data mining 
653 |a skills 
653 |a innovation 
653 |a sustainable agri-food systems 
653 |a filtering 
653 |a social and humanistic computing 
653 |a social impact 
653 |a analytics 
653 |a paradox 
653 |a lbsn 
653 |a big data 
653 |a knowledge management 
653 |a online data 
653 |a innovation in sustainable agriculture 
653 |a Social network 
653 |a educational data mining 
653 |a History of engineering & technology / bicssc 
653 |a spatial accessibility of residential public services 
653 |a place sustainability 
653 |a back-propagation neural network 
653 |a GDPR 
653 |a smart cities 
653 |a bibliometric analysis 
653 |a topic analysis 
653 |a social networks 
653 |a online community 
653 |a web science 
653 |a housing problem 
653 |a technopolitics 
653 |a promising technology 
653 |a hype cycle 
653 |a innovation networks 
653 |a policy 
653 |a context–problem network 
653 |a institutional innovation 
653 |a big data analytic methods 
653 |a online word-of-mouth 
653 |a KDE 
653 |a Greek Attica 
653 |a opinion mining 
653 |a social sciences 
653 |a GWR 
653 |a transaction costs 
653 |a prediction grades 
653 |a temporal analytics 
653 |a TripAdvisor 
653 |a destination image 
653 |a sales prediction 
653 |a illegal accommodation 
653 |a spatiotemporal analysis 
653 |a decision making 
653 |a framing 
653 |a research frontier 
653 |a sustainable development 
653 |a product attributes 
653 |a building stock management 
653 |a data science 
653 |a Xiamen City 
653 |a Hong Kong 
653 |a information systems 
653 |a user-generated content 
653 |a community detection 
653 |a decision-makers 
653 |a TP organics 
653 |a sentiment polarity classification 
653 |a semantic network analysis 
653 |a NodeXL 
653 |a technology platforms 
653 |a smart citizens 
653 |a data analyst 
653 |a decision-making 
653 |a social good 
653 |a social media 
653 |a sustainable wireless energy transmission technology 
653 |a online travel review 
653 |a text mining 
653 |a advanced business analytics 
653 |a network data analysis 
653 |a problem-solved concept 
653 |a sustainability development 
653 |a learning analytics 
653 |a researchers 
653 |a Guangzhou 
653 |a check-in density 
653 |a sentiment analysis 
653 |a maturity model 
653 |a early career 
653 |a social media big data 
653 |a point of interests (POI) 
653 |a Barcelona 
653 |a resource optimisation 
653 |a dynamic topic model 
653 |a experimental cities 
653 |a data commons 
653 |a review voting 
653 |a car review 
653 |a SDE 
653 |a association rule 
653 |a information diffusion 
653 |a systematic and replicable patent analysis method 
653 |a sustainability 
653 |a big data analytics 
653 |a social inclusive economic growth 
653 |a big data research 
653 |a framings 
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700 1 |a Chui, Kwok Tai 
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520 |a 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.