04844nam 22006375 450 991033771640332120200703094627.03-319-94105-410.1007/978-3-319-94105-9(CKB)4100000006674748(MiAaPQ)EBC5518694(DE-He213)978-3-319-94105-9(EXLCZ)99410000000667474820180917d2019 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierEmerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining /edited by Nitin Agarwal, Nima Dokoohaki, Serpil Tokdemir1st ed. 2019.Cham :Springer International Publishing :Imprint: Springer,2019.1 online resource (282 pages)Lecture Notes in Social Networks,2190-54283-319-94104-6 Chapter1: Intent Mining for the Good, Bad & Ugly Use of Social Web: Concepts, Methods, and Challenges -- Chapter2: Bot-ivistm: Assessing Information Manipulation in Social Media Using Network Analytics -- Chapter3: Studying Fake News via Network Analysis: Detection and Mitigation -- Chapter4: Predictive Analysis on Twitter: Techniques and Applications -- Chapter5: Using Subgraph Distributions for Characterizing Networks and Fitting Random Graph Models -- Chapter6: Towards Effective Assessment of Group Collaborations in OSNs -- Chapter7: Dynamics of Overlapping Community Structures with Application to Expert Identification -- Chapter8: On Dynamic Topic Models for Mining Social Media -- Chapter9: Domain Specific Use Cases for Knowledge Enabled Social Media Analysis -- Chapter10: Privacy in Human Computation: User awareness study, Implications for existing platforms, Recommendations, and Research Directions.The contributors in this book share, exchange, and develop new concepts, ideas, principles, and methodologies in order to advance and deepen our understanding of social networks in the new generation of Information and Communication Technologies (ICT) enabled by Web 2.0, also referred to as social media, to help policy-making. This interdisciplinary work provides a platform for researchers, practitioners, and graduate students from sociology, behavioral science, computer science, psychology, cultural studies, information systems, operations research and communication to share, exchange, learn, and develop new concepts, ideas, principles, and methodologies. Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining will be of interest to researchers, practitioners, and graduate students from the various disciplines listed above. The text facilitates the dissemination of investigations of the dynamics and structure of web based social networks. The book can be used as a reference text for advanced courses on Social Network Analysis, Sociology, Communication, Organization Theory, Cyber-anthropology, Cyber-diplomacy, and Information Technology and Justice.Lecture Notes in Social Networks,2190-5428Social sciences—Data processingSocial sciences—Computer programsData miningSociophysicsEconophysicsApplication softwareComputational Social Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/X34000Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Data-driven Science, Modeling and Theory Buildinghttps://scigraph.springernature.com/ontologies/product-market-codes/P33030Computer Appl. in Social and Behavioral Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/I23028Social sciences—Data processing.Social sciences—Computer programs.Data mining.Sociophysics.Econophysics.Application software.Computational Social Sciences.Data Mining and Knowledge Discovery.Data-driven Science, Modeling and Theory Building.Computer Appl. in Social and Behavioral Sciences.158.2Agarwal Nitinedthttp://id.loc.gov/vocabulary/relators/edtDokoohaki Nimaedthttp://id.loc.gov/vocabulary/relators/edtTokdemir Serpiledthttp://id.loc.gov/vocabulary/relators/edtBOOK9910337716403321Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining2518209UNINA