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Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining, 1st ed. 2019 Lecture Notes in Social Networks Series

Langue : Anglais

Coordonnateurs : Agarwal Nitin, Dokoohaki Nima, Tokdemir Serpil

Couverture de l’ouvrage Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining

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.


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.

Dr. Nitin Agarwal is a Distinguished Professor and Maulden-Entergy Endowed Chair of Information Science at the University of Arkansas at Little Rock.  He is also the Director of the Collaboratorium for Social Media and Online Behavioral Studies (COSMOS).  His research interests include social computing, deviant behavior modeling, mis/disinformation dissemination, computational propaganda analysis, group dynamics, social-cyber forensics, data mining, artificial intelligence, and privacy.  His research has been supported by the U.S. National Science Foundation (NSF), the Army Research Office (ARO), the Office of Naval Research (ONR), the Air Force Research Laboratory (AFRL), the Defense Advanced Research Projects Agency (DARPA), and the Department of Homeland Security (DHS) with a total funding of over $10 million.  He is a fellow of the prestigious International Academy, Research and Industry Association (IARIA).  Dr. Agarwal received his doctorate at theArizona State University in 2009 with outstanding dissertation recognition and was recognized as top 20 in their 20s by Arkansas Business.  He has published over 100 peer-reviewed articles with several best paper awards and has been recognized as an expert in social, cultural, and behavioral modeling by several international news media organizations.

Dr. Nima Dokoohaki is a senior data scientist. He is currently affiliated with Intellectera, a data science research & development company where together with co-founders he develops and delivers solutions for consumer behavior modeling and analytics. In addition, he maintains collaboration with a research group at Software and Computer Systems department of Royal Institute of Technology (KTH) as an external advisor. His research interests include trust & privacy, applied machine learning, social computing and recommendation systems. He received his Ph.D. in information and communications technology (ICT) in 2013. The m

Illuminates several fundamental and powerful yet theoretically obscure aspects of computational social network analysis Serves as a comprehensive reference for anyone interested in newer ICTs, examining their role in decision and policy making, understanding the dynamics of interaction, communication, and information propagation, and researching in social networks Provides an extensive repository of data sets and tools that can be used by researchers leading to a perpetual and synergistic advancement of the discipline

Date de parution :

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Date de parution :

Ouvrage de 278 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

52,74 €

Ajouter au panier