Online social networks: human cognitive constraints in Facebook and Twitter personal graphs

Online Social Networks: Human Cognitive Constraints in Facebook and Twitterprovides new insights into the structural properties of personal online social networks and the mechanisms underpinning human online social behavior. As the availability of digital communication data generated by social media is revolutionizing the field of social networks analysis, the text discusses the use of large- scale datasets to study the structural properties of online ego networks, to compare them with the properties of general human social networks, and to highlight additional properties. Users will find the data collected and conclusions drawn useful during design or research service initiatives that involve online and mobile social network environments.Provides an analysis of the structural properties of ego networks in online social networks Presents quantitative evidence of the Dunbar's number in online environmentsDiscusses original structural and dynamic properties of human social network through OSN analysis Dr. Valerio Arnaboldi Ph.D is currently a Researcher in the field of social networks analysis with the Ubiquitous Internet group of the Institute for Informatics and Telematics (IIT) of the National Research Council of Italy (CNR). Previously, he worked as a visiting Ph.D. student at the Social and Evolutionary Neuroscience Research Group at the University of Oxford (UK), under the supervision of Prof. Robin I.M. Dunbar. His research interests include social network analysis, social relationships modeling and context- and social-based services for networking solutions on mobile platforms.

This book provides insights into the structural properties of personal online social networks and the mechanisms underpinning human online social behavior. As the availability of digital communication data generated by social media is revolutionizing the field of social networks analysis. It discusses the use of large- scale datasets to study the structural properties of online ego networks, to compare them with the properties of general human social networks, and to highlight additional properties. Users will find the data collected and conclusions drawn useful during design or research service initiatives that involve online and mobile social network environments. It presents quantitative evidence of the Dunbar's number in online environments and discusses original structural and dynamic properties of human social network through OSN analysis. --