Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining / Lecture Notes in Social Networks (PDF)
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...
- Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
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.
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 main theme of his research was how to understand
Dr. Serpil Tokdemir is a research project analyst at the Office of Medicaid Inspector General (OMIG), Little Rock, Arkansas, USA. Dr. Tokdemir has a joint affiliation with the Collaboratorium for Social Media and Online Behavioral Studies (COSMOS) at UALR as research associate. Her work involves extracting raw data from Fraud and Abuse Detection System (FADS), cluster analysis, anomaly/outlier detection, predictive analysis and decision support systems, data visualization, content mining, and network analysis. Dr. Tokdemir obtained her PhD from UALR in 2015 with support from U.S. National Science Foundation (NSF). Bringing together the computational modeling and social science theories, her dissertation explored the role of social media in coordinating online collective action in the context of Saudi Arabian Women's campaigns for right to gender equality. She has published several articles in this domain and won the most published student distinction by Engineering and Information Technology college at UALR. She obtained her Bachelor in Science in Computer Science from Marmara University, Istanbul, Turkey in 2003. She completed her Master in Science (MS) in Computer Science from Georgia State University in 2006, Atlanta, Georgia, USA.
- 2018, 1st ed. 2019, 278 Seiten, Englisch
- Herausgegeben: Nitin Agarwal, Nima Dokoohaki, Serpil Tokdemir
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319941054
- ISBN-13: 9783319941059
- Erscheinungsdatum: 17.09.2018
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Grösse: 4.91 MB
- Ohne Kopierschutz
- Vorlesefunktion
Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
---|
Schreiben Sie einen Kommentar zu "Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining / Lecture Notes in Social Networks".
Kommentar verfassen