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Sentiment Analysis for Social Media

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ISBN: 9783039285723 / 9783039285730 Year: Pages: 152 DOI: 10.3390/books978-3-03928-573-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-06-09 16:38:56
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Abstract

Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection.

Big Data Research for Social Sciences and Social Impact

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ISBN: 9783039282203 9783039282210 Year: Pages: 416 DOI: 10.3390/books978-3-03928-221-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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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.

Keywords

big data --- illegal accommodation --- institutional innovation --- transaction costs --- housing problem --- building stock management --- Hong Kong --- information diffusion --- community detection --- topic analysis --- sentiment analysis --- social networks --- Social network --- sustainable development --- review voting --- online community --- paradox --- smart citizens --- experimental cities --- smart cities --- technopolitics --- big data --- Barcelona --- data commons --- decision-makers --- policy --- GDPR --- big data --- social sciences --- decision-making --- data analyst --- filtering --- framing --- big data --- maturity model --- temporal analytics --- advanced business analytics --- big data analytic methods --- semantic network analysis --- framings --- NodeXL --- promising technology --- research frontier --- bibliometric analysis --- hype cycle --- technology platforms --- sustainable agri-food systems --- innovation in sustainable agriculture --- online data --- data mining --- TP organics --- big data research --- point of interests (POI) --- sustainability development --- spatial accessibility of residential public services --- Xiamen City --- big data --- sales prediction --- online word-of-mouth --- dynamic topic model --- product attributes --- back-propagation neural network --- systematic and replicable patent analysis method --- problem-solved concept --- context–problem network --- network data analysis --- sustainable wireless energy transmission technology --- big data analytics --- text mining --- association rule --- car review --- skills --- researchers --- early career --- text mining --- social media big data --- lbsn --- check-in density --- spatiotemporal analysis --- KDE --- GWR --- SDE --- Guangzhou --- educational data mining --- learning analytics --- machine learning --- big data --- prediction grades --- destination image --- user-generated content --- online travel review --- big data analytics --- opinion mining --- sentiment analysis --- resource optimisation --- place sustainability --- TripAdvisor --- Greek Attica --- opinion mining --- social media --- social networks --- sentiment analysis --- sentiment polarity classification --- social impact --- big data research --- information systems --- analytics --- decision making --- social sciences --- big data research --- social and humanistic computing --- social sciences --- social good --- social impact --- machine learning --- knowledge management --- web science --- data science --- social inclusive economic growth --- sustainability --- innovation --- innovation networks

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MDPI - Multidisciplinary Digital Publishing Institute (2)


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2020 (2)