Small-world networks

Focusing on the phonological neighborhood defined by Turnbull and Peperkamp (2017: 83) as “two words are neighbors of each other if they differ by the deletion, addition or substitution of one and only one segment,” we analyzed the characteristics of phonological neighborhood networks (PNN) in English and Korean words in order to investigate the interrelation between words in these two languages. Here, a PNN is assumed to represent the mental lexicon. In the case of English, 33,329 high-frequency words were selected as target words from the Corpus of Contemporary American English (COCA) (Davies 2008), and in the case of Korean, 32,698 high-frequency words were selected as target words from SJ-RIKS (Kang and Kim 2009). Using R (R Core Team 2016) and Pajek (de Nooy et al. 2011), we formed the PNN matrices of both languages, and using these matrices, measured the key indicators of each language’s PNN, such as the number and size of sub-PNNs in each PNN, the proportion of the giant component size, average shortest path length, average clustering coefficient, and assortative mixing by degree (AMD). Through a quantitative analysis of these key indicators, it was shown that the network measurements reflect a language particularity between English and Korean, and at the same time the two PNNs shared the characteristics of a “small-world network” (Watts and Strogatz 1998) and a high value of AMD.

This paper is a culmination of an 11-month study of the independent electronic music scenes in Singapore in 2018. I analyse how independent music artists, producers, organisers, and fans from different facets of society produce social, cultural and financial capital for diverse stakeholders. While tethered to an array of musical genres and subcultures, these communities are united by their ideological orientation towards authenticity and distance from the mainstream market. I have gathered data through participant observation and semi-structured interviews with 32 scene participants, in order to analyse the values and opportunity structure within these different networks. Findings show how subcultural scenes fuel members' self-motivated learning, as well as generate networks with structural features shown to facilitate creativity and productivity. This study synthesises frameworks from several fields, namely educational psychology, subcultural theory, and social network studies. Analyses will be pertinent for social policy makers concerned about social stratification as it furthers the understanding of how spaces and social structures can support the diversifying of merit.

Most attempts to use the potentials of information technologies in benefit of the fulfilment of the democratic requirements from the local to the global levels are based on the power of social networks and the utilisation of big‐data approaches. However, both the network itself and the portliness of data processing have fundamental limitations that need to be overcome when the size of the population is larger than a reduced group. As to cope with the related complexity, the network provides in certain conditions a characteristic structure which facilitates the emergence of new functional features, and consequently a system. It is this structure –the fibres of the systemic relations– and new functionalities concerning the circulation of data what change the portliness of data processing into an appropriate percolation and management of relevant information. By these means complexity and the corresponding information flow are managed at the lowest possible level while cooperation and higher level management is ready to cope just with the excess of complexity the lower level cannot manage properly by itself. But this is the very idea of subsidiarity whose application to the organisation of heterogeneous societies has been a foundation of decentralised government since the 16 th century in many different contexts. At the age of the global information society, the necessary management of global issues (environment, geo‐politics, inequality, etc.) requires both proper levelism and information management from the peoples to communities, to national authorities, and to international institutions. Stafford Beer's Viable System Model provides a suitable approach to deploy subsidiarity with the backbone of an information and communication infrastructure based on the acquisition, circulation and processing of relevant information to enable decentralised, democratic decision‐making.

This paper offers a structured overview of 50 years of small-world research. Initially formulated by Pool and Kochen in the mid-1950s, the small-world concept can be divided into six research foci, based on three dimensions (structural, process-related, psychological), and two process-related themes (diffusion, search). Building on this analytical distinction, the article provides a historical summary of the different phases of research on the small-world problem, and summarizes the empirical and theoretical progress on different facets of the small-world phenomenon. The paper concludes with a brief assessment of accomplishments and open questions, suggesting some possible future research areas.

Small-world studies were introduced by Milgram and others in the 1960s and 1970s. These studies, and a majority of variants conducted by others, display a number of methodological weaknesses that bias their results. While no explicit methodological standard exists for these studies, here I derive a number of best-practice criteria for small-world studies by pointing out mistakes of previous studies, and by applying methodological standards from other empirical research areas. Improving the methodology of letter referral studies is important, because such studies could still be useful in a number of contexts today, especially for the exploration of factors affecting targeted search processes.

In this paper, we thoroughly investigate correlations of eigenvector centrality to five centrality measures, including degree centrality, betweenness centrality, clustering coefficient centrality, closeness centrality, and farness centrality, of various types of network (random network, small-world network, and real-world network). For each network, we compute those six centrality measures, from which the correlation coefficient is determined. Our analysis suggests that the degree centrality and the eigenvector centrality are highly correlated, regardless of the type of network. Furthermore, the eigenvector centrality also highly correlates to betweenness on random and real-world networks. However, it is inconsistent on small-world network, probably owing to its power-law distribution. Finally, it is also revealed that eigenvector centrality is distinct from clustering coefficient centrality, closeness centrality and farness centrality in all tested occasions. The findings in this paper could lead us to further correlation analysis on multiple centrality measures in the near future.

The benefits of using mathematical concepts are frequently overlooked in qualitative inquiry. In this paper, Graph Theory (GT) is applied to a series of two dimensional representations of the self used to illustrate the therapeutic progress of a suicidal youth and a young mother coping with depression. These self-maps are shown to be equivalent to GT networks with the self-map memes corresponding to GT vertices, the pair-wise relationships between memes corresponding to GT edges, and the time evolution of the self-mapping diagrams corresponding to GT sequence analysis. Consideration is given to the notion that the self so mapped functions as a small world network with emotive psychological triggers serving as “long range” connections. The advantages of using an interactive Graphical User Interface and GT metrics for client centered therapy and future research applications in social science are discussed.

El presente estudio además de analizar cuáles fueron las principales vías de aprovisionamiento de los productos de carácter suntuario más relevantes en los mercados romanos, pretende ofrecer al lector un nuevo escenario para el debate mediante la incorporación de las teorías de redes a un tema ya de por sí bastante prolífico: el comercio de productos orientales. Así, por primera vez, el uso de las crónicas chinas, junto con las fuentes clásicas (romanas), nos ha permitido comprobar
hasta qué punto existió similitud en los comentarios sobre las riquezas de la región que comprenden los territorios de Egipto y Próximo Oriente. Si a esta concomitancia le sumamos los resultados obtenidos por las teorías de redes, en particular las desarrolladas por Stanley Milgram en 1967, nos percatamos de la existencia de una serie de ciudades entre continentes que destacaron por su paso obligado, a modo de “superconectores” o hubs, como principales mercados suntuarios.

In this paper, we propose word sense disambiguation methods based on lexical substitution and used for the task 1 of the SemDis2014 workshop. This methods are run by using short random walks on unipartite networks or bipartite networks. Some of these methods only use graphs automatically built from corpora (unsurpervised methods), others also use graphs built from handcraft resources filled by lexicographers or by the crowds (supervised methods).

Purpose – The aim of this paper is to offer agent-based modelling (ABM) as an alternative approach to advance research in entrepreneurship. It argues that ABM allows entrepreneurship researchers (i.e. the designers) to find better ways in generating entrepreneurial outcomes by understanding alternative histories and examining a plausible future.

Design/methodology/approach – This paper begins with an overview of ABM, and discusses the shared conceptual foundations of entrepreneurship and ABM as the motives for the adoption of ABM as an appropriate methodology to study entrepreneurship. It offers a roadmap in using ABM approach for entrepreneurship research and illustrates this using a contemporary research question in entrepreneurship: the study of success/failure in business venturing.

Findings – This paper suggests the shared foundations between ABM and entrepreneurship as the basis for bringing the methodology and research domain closer. It offers a roadmap for advancing entrepreneurship research using agent-based simulation approach and explains the contribution of ABM to further advance entrepreneurship research.

Originality/value – This paper addresses the methodological gap in entrepreneurship research and develops the argument for a wider adoption of ABM simulation approach to study entrepreneurship. It bridges the gap by examining the possibility of formalizing entrepreneurship processes by grounding an agent-based model on empirical facts and generally-accepted foundations of entrepreneurship. It offers a contribution to the literature by showing that ABM is a useful and appropriate methodological approach for entrepreneurship research in addition to the conventional variance and process approach.

In recent years network analysis has been applied in archaeological research to examine the structure of archaeological relationships of whatever sort. However, these archaeological applications share a number of issues concerning 1) the role of archaeological data in networks; 2) the diversity of network structures, their consequences and their interpretation; 3) the critical use of quantitative tools; 4) the influence of other disciplines, especially sociology. This article concerns a deconstruction of past archaeological methods for examining networks. Through a case-study of Roman table wares in the Eastern Mediterranean, the article will highlight a number of issues with network analysis as a method for archaeology. It urges caution with the uncritical application of network analysis methods developed in other disciplines and applied to archaeology. However, it stresses the potential benefits of network analysis for the archaeological discipline and acknowledges the need for developing a specifically archaeological network analysis, which should be based on relational thinking and can be expanded with an archaeological toolset for quantitative analysis

Since the mid-1990s has emerged a new research field, webometrics, investigating the nature and properties of the Web drawing on modern informetric methodologies. The article attempts to point to selected areas of webometric research that demonstrate interesting progress and space for development as well as to some currently less promising areas. Recent investigations of search engine coverage and performance are reviewed as a frame for selected quality and content analyses. Problems with measuring Web Impact Factors (Web-IF) are discussed. Concluding the article, new directions of webometrics are outlined for performing knowledge discovery and issue tracking on the Web, partly based on bibliometric methodologies used in bibliographic and citation databases. In this framework graph theoretic approaches, including path analysis, transversal links, "weak ties" and "small-world" phenomena are integrated.

Despite many decades of study, scientists
still puzzle over the process of insight. By what mechanism
does a person experience that “Aha!” moment,
when sudden clarity emerges from a tangled web of
thoughts and ideas? This research integrates psychological
work on insight with graph theoretic work on
“small-world” phenomenon, to construct a theory that
explains how insight occurs, how it is similar to and
different from more typical learning processes, and
why it yields an affective response in the individual. I
propose that cognitive insight occurs when an atypical
association, forged through random recombination or
directed search, results in a “shortcut” in an individual’s
network of representations. This causes a rapid
decrease in path length, reorients the individual’s understanding of the relationships within and among the
affected representations, and can prompt a cascade of
other connections. This result is demonstrated by applying
graph theoretical analysis to network translations
of commonly used insight problems.

In this work, we use a complex network approach to investigate how a neural network structure changes under synaptic plasticity. In particular, we consider a network of conductance-based, single-compartment integrate-and-fire excitatory and inhibitory neurons. Initially the neurons are connected randomly with uniformly distributed synaptic weights. The weights of excitatory connections can be strengthened or weakened during spiking activity by the mechanism known as spike-timing-dependent plasticity (STDP). We extract a binary directed connection matrix by thresholding the weights of the excitatory connections at every simulation step and calculate its major topological characteristics such as the network clustering coefficient, characteristic path length and small-world index. We numerically demonstrate that, under certain conditions, a nontrivial small-world structure can emerge from a random initial network subject to STDP learning.

Abstract: The recent economic downturn has increased the need for cooperation among carriers in the container shipping industry. We introduce in this work a network analysis to investigate the topology and hierarchical structure of inter-carrier relationships. Our dataset is comprised of 65 carriers that provide 604 container services. Main findings indicate that the Cooperative Container Network (CCN) belongs to the family of small world networks. We demonstrate that when we increase the value of the connectivity among carriers, the ...

Directed scale free network is a network which exists in WWW (World Wide Web), phone call, E.Coli. metabolism, etc. There are many network measures which are used to apply on directed scale free network but it is not known how much they are statistical dependent or correlated (statistically similar) with each other. In our research, we selected 12 popular social network measures which were applied on 48,945 directed scale free network graphs (almost all types of directed scale free network) which are generated by "Bela Bollobas, Christian Borgsy, Jennifer Chayesz, Oliver Riordanx's directed scale free graph" algorithm [1] and found out how much correlated these 12 social network measures with each other by using PEARSON CORRELATION. Then we found out which is better for computation time among correlated measures .We found out 9 measures are highly correlated among 12 measures. Our Core_i7 processor computer needed more than 112 hours (4 days 16 hours) to find out highly correlated measures for directed scale free network .

Purpose: Purpose of the present paper was to identify prolific and influential researchers in digital library domain in Iran. It tries to determine the extent of research collaborations of the scientific community of Iranian digital libraries (DLs) domain in scientific conferences and journals.
Methodology: This is a scientometrics applied study. In this regard, Social Network Analysis (SNA) methods were used to analyze and visualize the co-authorship structure. The statistical population of this research includes all researchers affiliated with Iranian institutions which wrote at least one Persian or English languages paper up to 2016 in the DLs domain. Microsoft Excel, RavarMatrix and UCINet softwares has been utilized to analyze the collected data. Also, NodeXL and VOSviewer softwares were applied in order to mapping the co-authorship networks.
Findings: Researchers productivity is not in agreement with Lotka's Law; In addition, the findings showed international collaboration that the low level and dominant authorship pattern in DLs domain papers is a two-author model. Overall and by taking into account the average rating of all scientific production and SNA indicators, respectively Mehdi Alipour-hafezi, Yaghoub Norouzi, Saeed Rezaei Sharifabadi are Iranian key actors in the DLs domain.
Conclusion: Co-authorship network of DLs domain in Iran, seems to exhibit “scale-free” network properties and the very low density of the network also indicates the inadequate maturity of the researchers' social structure; However, still the Milgram's six degrees of separation theory is verificatied about this community and the utilization of the term “small world network” it's permissible.
هدف: این مقاله به شناسایی پژوهشگران پرکار و بانفوذ و همچنین تعیین حدود و ثغور همکاری‏ های پژوهشی جامعه علمی حیطه کتابخانه های دیجیتالی ایران پرداخته است.
روش ‏شناسی: مطالعه حاضر از نوع پژوهش‏ های کاربردی علم‏ سنجی می‏ باشد که با روش تحلیل شبکه‏ های اجتماعی به انجام رسیده است. جامعه آماری این پژوهش، شامل تمامی پژوهشگران وابسته به نهادهای ایرانی می‏‏ باشد که دست‏ کم یک مقاله فارسی یا انگلیسی تا انتهای سال‏ های 1395 یا 2016 در حوزه کتابخانه دیجیتالی تألیف کرده‏ اند. داده های گردآوری شده با نرم افزارهای اکسل، راورماتریس و یوسی‏ آی‏ نت تحلیل شدند. همچنین، به‏ منظور ترسیم نقشه‏ های هم‏ تألیفی از نرم‏ افزارهای نودایکس‌ال و وی‏ اُ‏ اِس ‏ویوور کمک گرفته شد.
یافته‏ ها: بهره‏ وری پژوهشگران با قانون لوتکا موافق نیست؛ علاوه‏ بر این، یافته‏ ها از پایین بودن سطح همکاری‌های بین‌المللی حکایت داشت و الگوی نویسندگی غالب مقالات دو‏نویسنده‏ ای بود. به‏ طور کلی و با احتساب میانگین امتیاز تمامی شاخص های تولید و مرکزیت شبکه های اجتماعی، به ترتیب مهدی علیپور حافظی، یعقوب نوروزی، سعید رضایی شریف‏ آبادی بازیگران کلیدی در مرجعیت علمی حوزه کتابخانه های دیجیتالی ایران هستند.
نتیجه‏ گیری: شبکه هم تألیفی حوزه کتابخانه های دیجیتالی، نوعی شبکه آزاد مقیاس بوده و چگالی خیلی پایین شبکه نیز دال بر عدم بلوغ کافی ساختار اجتماعی پژوهشگران می‏ باشد؛ با این وجود، هنوز نظریه شش درجه جدایی میلگرام درباره این جامعه مورد تصدیق قرار می‏ گیرد و به کارگیری اصطلاح «شبکه جهان کوچک» در مورد آن جایز است.

Our primary objective in this paper is to study the distribution of the maximal clique size of the vertices in complex networks. We define the maximal clique size for a vertex as the maximum size of the clique that the vertex is part of and such a clique need not be the maximum size clique for the entire network. We determine the maximal clique size of the vertices using a modified version of a branch-and-bound based exact algorithm that has been originally proposed to determine the maximum size clique for an entire network graph. We then run this algorithm on two categories of complex networks: One category of networks capture the evolution of small-world networks from regular network (according to the well-known
Watts-Strogatz model) and their subsequent evolution to random networks; we show that the distribution of the maximal clique size of the vertices follows a Poisson-style distribution at different stages of the evolution of the small-world network to a random network; on the other hand, the maximal clique size of
the vertices is observed to be in-variant and to be very close to that of the maximum clique size for the entire network graph as the regular network is transformed to a small-world network. The second category of complex networks studied are real-world networks (ranging from random networks to scale-free
networks) and we observe the maximal clique size of the vertices in five of the six real-world networks to follow a Poisson-style distribution. In addition to the above case studies, we also analyze the correlation between the maximal clique size and clustering coefficient as well as analyze the assortativity index of the vertices with respect to maximal clique size and node degree.

‘Small-world’ networks have been widely studied recently in many fields that use network analysis and the implications are often dramatic. The most common use of networks in political science occurs in the policy network literature, however, networks that form policy tend to be much smaller than the usual networks that we see in small-world investigations. It is not immediately apparent whether the theory will transfer to this particular application with the usual dramatic impact. This paper summarises the current state of play in small-world theory and examines the implications of taking the theory into the smaller decision making networks found in policy making. The tests for a small- world are applied to some of the very few suitable political network datasets.

Combining webometric and social network analytic approaches, this study developed a methodology to sample and identify Web links, pages, and sites that function as small-world connectors affecting short link distances along link paths between different topical domains in an academic Web space. The data set comprised 7669 subsites harvested from 109 UK universities. A novel corona-shaped Web graph model revealed reachability structures among the investigated subsites. Shortest link path nets functioned as investigable small-world link structures – ‘mini small worlds’ – generated by deliberate juxtaposition of topically dissimilar subsites. Indicative findings suggest that personal Web page authors and computer science subsites may be important small-world connectors across sites and topics in an academic Web space. Such connectors may counteract balkanization of the Web into insularities of disconnected and unreachable subpopulations.

Networks have been widely adopted in political science, particularly in connection with governance and with the process of policy formation. Every study, if it forms part of this universe, bases itself on adopting a network ‘world view’: all studies start with the assumption that ‘there is a network here’. Dispiritingly few go on to explain, justify or discuss the implications of this assumption with reference to the assumption; in contrast this thesis intentionally regresses back to a detailed look at first principles.
This thesis develops and presents a new and valuable approach to the formal analysis of networks that form policy. The approach is drawn out of a theoretical consideration of the policy process and examined in the context of existing policy network literature.
A test of the usefulness of the approach is made by application to a case. There are therefore two intertwined threads of content built around the topic of pension reform. The formal analysis of a network of actors is presented alongside a ‘traditional’ case- study approach to the policy-making process for the UK and France. These two analyses
contribute to an assessment of the comparative advantages of the two methods. The thesis is constructed with the intention of clearly presenting a new analytical approach that can be adopted by other researchers and ensuring that it is adequately justified so that it will be adopted.

The analysis of the brain in terms of integrated neural networks may offer insights on the reciprocal relation between structure and information processing. Even with inherent technical limits, many studies acknowledge neuron spatial arrangements and communication modes as key factors. In this perspective, we investigated the functional organization of neuronal networks by explicitly assuming a specific functional topology, the small-world network. We developed two different computational approaches. Firstly, we asked whether neuronal populations actually express small-world properties during a definite task, such as a learning task. For this purpose we developed the Inductive Conceptual Network (ICN), which is a hierarchical bio-inspired spiking network, capable of learning invariant patterns by using variable-order Markov models implemented in its nodes. As a result, we actually observed small-world topologies during learning in the ICN. Speculating that the expression of small-world networks is not solely related to learning tasks, we then built a de facto network assuming that the information processing in the brain may occur through functional small-world topologies. In this de facto network, synchronous spikes reflected functional small-world network dependencies. In order to verify the consistency of the assumption, we tested the null-hypothesis by replacing the small-world networks with random networks. As a result, only small world networks exhibited functional biomimetic characteristics such as timing and rate codes, conventional coding strategies and neuronal avalanches, which are cascades of bursting activities with a power-law distribution. Our results suggest that small-world functional configurations are liable to underpin brain information processing at neuronal level.

Networks have been widely adopted in political science, particularly in connection with governance and with the process of policy formation. Every study, if it forms part of this universe, bases itself on adopting a network 'world view': all studies start with the assumption that 'there is a network here'. Dispiritingly few go on to explain, justify or discuss the implications of this assumption with reference to the assumption; in contrast this thesis intentionally regresses back to a detailed look at first principles. This thesis develops and presents a new and valuable approach to the formal analysis of networks that form policy. The approach is drawn out of a theoretical consideration of the policy process and examined in the context of existing policy network literature. A test of the usefulness of the approach is made by application to a case. There are therefore two intertwined threads of content built around the topic of pension reform. The formal analysis of...

Many real-world applications can be modelled as complex networks, and such networks include the Internet, epidemic disease networks, transport networks, power grids, protein-folding structures and others. Network integrity and ro-bustness are important to ensure that crucial networks are protected and un-desired harmful networks can be dismantled. Network structure and integrity can be controlled by a set of key nodes, and to find the optimal combination of nodes in a network to ensure network structure and integrity can be an NP-complete problem. Despite extensive studies, existing methods have many limitations and there are still many unresolved problems. This paper presents a probabilistic approach based on neighborhood information and node importance , namely, neighborhood information-based probabilistic algorithm (NIPA). We also define a new centrality-based importance measure (IM), which combines the contribution ratios of the neighbor nodes of each target node and two-hop node information. Our proposed NIPA has been tested for different network benchmarks and compared with three other methods: optimal attack strategy (OAS), high betweenness first (HBF) and high degree first (HDF). Experiments suggest that the proposed NIPA is most effective among all four methods. In general, NIPA can identify the most crucial node combination with higher effectiveness , and the set of optimal key nodes found by our proposed NIPA is much smaller than that by heuristic centrality prediction. In addition, many previously neglected weakly connected nodes are identified, which become a crucial part of the newly identified optimal nodes. Thus, revised strategies for protection are recommended to ensure the safeguard of network integrity. Further key issues and future research topics are also discussed. Citation Details: Qian Li, San-Yang Liu, Xin-She Yang, Neighborhood information-based prob-abilistic algorithm for network disintegration, Expert Systems with Applications,

Neste artigo, analisamos as propriedades estatísticas e estruturais da rede de transporte aéreo mundial, modelada como uma rede complexa. Esta análise permite compreender a topologia da rede e compará-la a tipos de redes já conhecidas. Obtemos que a rede aérea mundial se caracteriza tanto como uma rede de mundo pequeno quanto uma rede sem escala, além de refletir características geopolíticas e de se mostrar muito resistente à ataques e erros.

In this article, we analyze the statistical and structural properties of the world-wide airport network, studied as a complex network. This analysis allows us to understand the topology of the network and compare it to known networks. We find out that the world-wide airport network is both a small-world network and a scale-free network. Moreover, it reflects geopolitical characteristics and is highly resistant to errors and attacks.

The internet rapid growth, stimulate the emergence of start-up companies based on information technology and telecommunication (ICT) in Indonesia and Singapore. As the number of start-ups and its investor growth, the network of its relationship become larger and complex, but on the other side feel small. Everyone in the ICT start-up investment network can be reached in short steps, led to a phenomenon called small world phenomenon, a principle that we are all connected by a short chain of relationships. We investigate the pattern of the relationship between start-up with its investor and the small world characteristics using network analysis methodology. The research is conducted by creating the ICT start-up investment network model of each country and calculate its small world network properties to see the characteristic of the networks. Then we compare and analyse the result of each network model. The result of this research is to give knowledge about the current condition of ICT start-up investment in Indonesia and Singapore. The research is beneficial for business intelligence purpose to support decision making related to ICT start-up investment.

Based on 2012-data about international trade, an export/import world network is built. We carry on a basic complex network analysis on it, determining basic metrics. No economic analysis is intended. As expected, the network displays small-world properties and globalization patterns.

For at least the last 5,000 years, competition for social and economic control led to the acquisition of social power and wealth by some individuals or groups and the emergence of complex social systems.  This paper will present the preliminary results of a larger study intended to identify the changing network structures that underlie society at the household, village and regional scales and led to the emergence of social complexity as a system level phenomenon during the Prehistoric Bronze Age on Cyprus (2400-1700 Cal BCE).  Using data from previously excavated settlements and cemeteries as proxies for  multiple facets of social and economic inequality including differential access to resources, labor and exchange networks, this research quantifies wealth based on Gini Coefficients and identifies changes in social networks and the emergence of social complexity through time and across space.  It incorporates theories and methodologies developed in the interdisciplinary field of complex systems science and network theory in conjunction with anthropological thinking.  The results of this work will give us a better understanding of how social complexity emerges and changes in middle-range society and offers us a more in-depth understanding of the Prehistoric Bronze Age on Cyprus.  Further, it offers archaeologists new methodology and theory for approaching and identifying this facet of human social behavior.