Real world systems like biological, social, technological, infrastructural and many others can be modeled as networks. The field of network science aims to study these complex networks and understand their structure and dynamics. A common feature of networks across domains is the distribution of the degree of the nodes according to a power-law (scale invariance). As a consequence of this skewness, the high degree nodes dominate the properties of these networks. The rich-club phenomenon is observed when the high degree or the rich nodes of the network prefer to connect amongst themselves. In the first part, the thesis investigates the rich-club phenomenon in higher order neighborhoods of the network by providing an elegant quantification using a geodesic distance based approach. This quantification helped in identifying networks where the trend and intensity of the rich-club phenomenon is significantly different in higher order neighborhoods compared to the immediate neighbors. The thesis also proposes a quantification of the importance of the non-rich nodes in the communication structure of the rich nodes, and broadly classify networks into core-periphery or cellular. Further a lack of universality is noticed in the structure of the networks belonging to a particular domain. It has been observed in the previous literature that the rich club connectivity dominates assortativity, a measure quantifying the mixing patterns in complex networks. Thus, assortativity is biased. To overcome such drawbacks, in the second part of the thesis proposes a novel measure called regularity. The analytical bounds on regularity and formulation of regularity for different network models are provided. Along with this a measure to quantify the mixing patterns of the neighborhood of a node called local regularity is also defined. The analysis on real-world network based on local regularity and degree distribution shows presence of both type of network, uniformly and non-uniformly mixed across different regions. Further normalized regularity is proposed to quantify the extent of preferential mixing in networks discounting the effect of degree distribution.

Purpose/Aim: To find power structures within the blog network. Material/Method: Using keywords to find all available blog posts about the National Defence Radio Establishment from the blog search engine Twingly, and thereafter using the same blog search engine to find inlinks from other blogs, to those posts. The data is set into the context of the small-world networks models of Duncan J. Watts and rich-club models of Sergi Valverde och Ricard V. Sole. Main results: 5183 unique blogs have written about the subject in 22779 blog posts to which 28128 inlinks from other blogposts are made. Just over one fifth of the blogs are linkted to each other in one big network, where the remaining blogs stand without any ingoing or outgoing links. The first bloggers are the one who continue to write for longer period of time and also the ones who attracts most inlinks. The blogosphere around this subject is highly connected, shows features as one would find in a small-world network, displays a power-law distribution for inlinks and is highly clustered around a few rich- club nodes.

Evolutionary Psychology (EP) tends to be associated with a Massively Modular (MM) cognitive architecture. I argue that EP favors a non-MM cognitive architecture. The main point of dispute is whether central cognition, such as abstract reasoning, exhibits domain-general properties. Partisans of EP argue that domain-specific modules govern central cognition, for it is unclear how the cognitive mind could have evolved domain-generality. In response, I defend a distinction between exogenous and endogenous selection pressures, according to which exogenous pressures tend to select for domain-specificity, whereas the latter, endogenous pressures, select in favor of domain-generality. I draw on models from brain network theory to motivate this distinction, and also to establish that a domain-general, non-MM cognitive architecture is the more parsimonious adaptive solution to endogenous pressures.