Search results for "Degree distribution"
showing 3 items of 13 documents
The Footprints of a “Mastodon”: How a Decentralized Architecture Influences Online Social Relationships
2019
Decentralized online social networks (DOSNs) have recently emerged as a viable solution to preserve the users' privacy and ensure higher users' control over the contents they publish. However, little is known about the backlashes that the decentralized organization and management of these platforms may have on the overlaid social network. This paper fills the gap. Specifically, we investigate how a decentralized architecture based on distributed servers impacts the structure of the users' neighborhood and their ego-networks. Our analysis relies on social data gathered from the decentralized micro-blogging platform Mastodon, the newest and fastest-growing decentralized alternative to Twitter…
Correcting for the study bias associated with protein-protein interaction measurements reveals differences between protein degree distributions from …
2015
Protein–protein interaction (PPI) networks are associated with multiple types of biases partly rooted in technical limitations of the experimental techniques. Another source of bias are the different frequencies with which proteins have been studied for interaction partners. It is generally believed that proteins with a large number of interaction partners tend to be essential, evolutionarily conserved, and involved in disease. It has been repeatedly reported that proteins driving tumor formation have a higher number of PPI partners. However, it has been noticed before that the degree distribution of PPI networks is biased toward disease proteins, which tend to have been studied more often …
Structural Dynamics of Interfirm Knowledge Networks
2016
In this chapter, we investigate the drivers of interfirm network structural dynamics and their influence on knowledge creation and diffusion processes that occur in such networks over time. Interfirm knowledge networks are complex webs of linkages connecting a variety of idiosyncratic firms within and across industries. Aimed to contribute to answer the recent calls for a more dynamic and multilevel view to understand network structures and processes, we leverage the complex network research to formulate a multilevel theoretical framework that clarifies the structural dynamics and knowledge creation and diffusion potential of interfirm networks.