Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.

Does Network Theory Contradict Trait Theory

Abstract: I argue that the trait and network theories of personality are not necessarily contradictory. If appropriately formalized, it may turn out that network theory incorporates traits as part of the the...

What do we need to add to a social network to get a society? Answer: something like what we have to add to a spatial network to get a city

Abstract: Recent years have seen great advances in social network analysis. Yet, with a few exceptions, the field of network analysis remains remote from social theory. As a result, much social network research, while technically accomplished and theoretically suggestive, is essentially descriptive. How then can social networks be linked to social theory ? Here we pose the question in its simplest form: what must we add to a social network to get a society ? We begin by showing that one reason for the disconnection between network theory and society theory is that because it exists in spacetime, the concept of social network raises the issue of space in a way that is problematical for social theory. Here we turn the problem on its head and make the problem of space in social network theory explicit by proposing a surprising analogy with the question: what do you have to add to an urban space network to get a city. We show first that by treating a city as a naive spatial network in the first instance and allowing it to acquire two formal properties we call reflexivity and nonlocality, both mediated through a mechanism we call description retrieval, we can build a picture of the dynamics processes by which collections of the buildings become living cities. We then show that by describing societies initially as social networks in space-time and adding similar properties, we can construct a plausible ontology of a simple human society. The problem: societies as space-time networks For much of the twentieth century, the concept of network was among the most fertile sources of empirical insights into the working of societies (for overviews see Albrecht, Fitzpatrick & Scrimshaw 2000, Poole & Kochen 1978; also Fischer 1976, Granovetter 1982). The concept had the dual advantage of being both readily quantifiable and permitting the direct investigation of the society as it appears in space-time. More than any other, the concept of network offered to put sociology on the kind of foundation we associate with orthodox science by linking mathematical expression to empirical testing. At the start of the twenty first century it is the concept of social network, and its comparability of networks occurring in the natural world, that has brought sociology into the common realm of scientific discourse. (for example Amaral et al 2004. Watts 2003)

Centrality metrics and line-graph to measure the importance of links in online social networks

Abstract: Importance of nodes and tie strength are necessary elements to characterize and analyze networks, as well as to study the processes that occur in their interior. We believe that it is also necessary to know the importance of links to have a better characterization of the networks in the study of those processes. In response to this situation, we propose a method to measure the importance of the links.The method is based on applying the line-graph mathematical concept to the graph representing the network, thus we create a new graph in which we apply centrality metrics to find the importance of network links.

A Hubterranean View of Syntax: An Analysis of Linguistic Form Through Network Theory

Abstract: Language is part of nature, and as such, certain general principles that generate the form of natural systems, will also create the patterns found within linguistic form. Since network theory is one of the best theoretical frameworks for extracting general principles from diverse systems, this thesis examines how a network perspective can shed light on the characteristics and the learning of syntax. It is demonstrated that two word co-occurrence networks constructed from adult and child speech (BNC World Edition 2001; Sachs 1983; MacWhinney 2000a) exhibit three non-atomic syntactic primitives namely, the truncated power law distributions of frequency, degree and the link length between two nodes (the link representing a precedence relation). Since a power law distribution of link lengths characterises a hubterranean structure (Kasturirangan 1999) i.e. a structure that has a few highly connected nodes and many poorly connected nodes, both the adult and the child word co-occurrence networks exhibit hubterranean structure. This structure is formed by an optimisation process that minimises the link length whilst maximising connectivity (Mathias & Gopal 2001 a&b). The link length in a word co-occurrence network is the storage cost of representing two adjacently co-occurring words and is inversely proportion to the transitional probability (TP) of the word pair. Adjacent words that co-occur often together i.e. have a high TP, exhibit a high cohesion and tend to form chunks. These chunks are a cost effective method of storing representations. Thus, on this view, the (multi-) power law of link lengths represents the distribution of storage costs or cohesions within adjacent words. Such cohesions form groupings of linguistic form known as syntactic constituents. Thus, syntactic constituency is not specific to language and is a property derived from the optimisation of the network. In keeping with other systems generated by a cost constraint on the link length, it is demonstrated that both the child and adult word co-occurrence networks are not hierarchically organised in terms of degree distribution (Ravasz and Barabasi 2003:1). Furthermore, both networks are disassortative, and in line with other disassortative networks, there is a correlation between degree and betweenness centrality (BC) values (Goh, Kahng and Kim 2003). In agreement with scale free networks (Goh, Oh, Jeong, Kahng and Kim 2002), the BC values in both networks follow a power law distribution. In this thesis, a motif analysis of the two word co-occurrence networks is a richly detailed (non-functional) distributional analysis and reveals that the adult and child significance profiles for triad subgraphs correlate closely. Furthermore, the most significant 4-node motifs in the adult network are also the most significant in the child network. Utilising this non-functional distributional analysis in a word co-occurrence network, it is argued that the notion of a general syntactic category is not evidenced and as such is inadmissible. Thus, non-general or construction-specific categories are preferred (in line with Croft 2001). Function words tend to be the hub words of the network (see Ferrer i Cancho and Sole 2001a), being defined and therefore identified by their high type and token frequency. These properties are useful for identifying syntactic categories since function words are traditionally associated with particular syntactic categories (see Cann 2000). Consequently, a function word and thus a syntactic category may be identified by the interception of the frequency and degree power laws with their truncated tails. As a given syntactic category captures the type of words that may co-occur with the function word, the category then encourages consistency within the functional patterns in the network and re-enforces the network’s (near-) optimised state. Syntax then, on this view, is both a navigator, manoeuvring through the ever varying sea of linguistic form and a guide, forging an uncharted course through novel expression. There is also evidence suggesting that the hubterranean structure is not only found in the word co-occurrence network, but within other theoretical syntactic levels. Factors affecting the choice of a verb that is generalised early relate to the formation and the characteristics of hubs. In that, the property of a high (token) frequency in combination with either a high degree (type frequency) or a low storage cost, point to certain verbs within the network and these highly ‘visible’ verbs tend to be generalised early (in line with Boyd and Goldberg forthcoming). Furthermore, the optimisation process that creates hubterranean structure is implicated in the verb-construction subpart network of the adult’s linguistic knowledge, the mapping of the constructions’ form-to-meaning pairings, the construction inventory size as well as certain strategies aiding first language learning and adult artificial language learning.