Termeh Shafie

Investigating human geographic origins using dual-isotope (87Sr/86Sr, δ18O) assignment approaches.

Substantial progress in the application of multiple isotope analyses has greatly improved the ability to identify nonlocal individuals amongst archaeological populations over the past decades. More recently the development of large scale models of spatial isotopic variation (isoscapes) has contributed to improved geographic assignments of human and animal origins. Persistent challenges remain, however, in the accurate identification of individual geographic origins from skeletal isotope data in studies of human (and animal) migration and provenance. In an attempt to develop and test more standardized and quantitative approaches to geographic assignment of individual origins using isotopic data two methods, combining 87Sr/86Sr and δ18O isoscapes, are examined for the Circum-Caribbean region: 1) an Interval approach using a defined range of fixed isotopic variation per location; and 2) a Likelihood assignment approach using univariate and bivariate probability density functions. These two methods are tested with enamel isotope data from a modern sample of known origin from Caracas, Venezuela and further explored with two archaeological samples of unknown origin recovered from Cuba and Trinidad. The results emphasize both the potential and limitation of the different approaches. Validation tests on the known origin sample exclude most areas of the Circum-Caribbean region and correctly highlight Caracas as a possible place of origin with both approaches. The positive validation results clearly demonstrate the overall efficacy of a dual-isotope approach to geoprovenance. The accuracy and precision of geographic assignments may be further improved by better understanding of the relationships between environmental and biological isotope variation; continued development and refinement of relevant isoscapes; and the eventual incorporation of a broader array of isotope proxy data.

Nation Building and Social Signaling in Southern Ontario : A.D. 1350–1650

Pottery is a mainstay of archaeological analysis worldwide. Often, high proportions of the pottery recovered from a given site are decorated in some manner. In northern Iroquoia, late pre-contact pottery and early contact decoration commonly occur on collars—thick bands of clay that encircle a pot and extend several centimeters down from the lip. These decorations constitute signals that conveyed information about a pot’s user(s). In southern Ontario the period A.D. 1350 to 1650 witnessed substantial changes in socio-political and settlement systems that included population movement, coalescence of formerly separate communities into large villages and towns, waxing and waning of regional strife, the formation of nations, and finally the development of three confederacies that each occupied distinct, constricted areas. Social network analysis demonstrates that signaling practices changed to reflect these regional patterns. Networks become more consolidated through time ultimately resulting in a “small world” network with small degrees of separation between sites reflecting the integration of communities within and between the three confederacies.

Data Protection for Online Social Networks and P -Stability for Graphs

Graphs can be used as a model for online social networks. In this framework, vertices represent individuals and edges relationships between individuals. In recent years, different approaches have been considered to offer data privacy to online social networks and for developing graph protection. Perturbative approaches are formally defined in terms of perturbation and modification of graphs. In this paper, we discuss the concept of P -stability on graphs and its relation to data privacy. The concept of P -stability is rooted in the number of graphs given a fixed degree sequence. In this paper, we show that for any graph there exists a class of P -stable graphs. This result implies that there is a fully polynomial randomized approximation for graph masking for the graphs in the class. In order to further refine the classification of a given graph, we introduce the concept of natural class of a graph. It is based on a class of scale-free networks.

Multivariate Entropy Analysis of Network Data

Multigraphs with numerical or qualitative attributes defined on vertices and edges can benefit from systematic methods based on multivariate entropies for describing and analysing the interdependencies that are present between vertex and edge attributes. This is here illustrated by application of these tools to a subset of data on the social relations among Renaissance Florentine families collected by John Padgett. Using multivariate entropies we show how it is possible to systematically check for tendencies in data that can be described as independencies or conditional independencies, or as dependencies allowing certain combinations of variables to predict other variables. We also show how different structural models can be tested by divergence measures obtained from the multivariate entropies.

Analyzing local and global properties of multigraphs

ABSTRACT The local structure of undirected multigraphs under two random multigraph models is analyzed and compared. The first model generates multigraphs by randomly coupling pairs of stubs according to a fixed degree sequence so that edge assignments to vertex pair sites are dependent. The second model is a simplification that ignores the dependency between the edge assignments. It is investigated when this ignorance is justified so that the simplified model can be used as an approximation, thus facilitating the structural analysis of network data with multiple relations and loops. The comparison is based on the local properties of multigraphs given by marginal distribution of edge multiplicities and some local properties that are aggregations of global properties.

Reconstructing Archaeological Networks with Structural Holes

Model-based reconstruction is an approach to infer network structures where they cannot be observed. For archaeological networks, several models based on assumptions concerning distance among sites, site size, or costs and benefits have been proposed to infer missing ties. Since these assumptions are formulated at a dyadic level, they do not provide means to express dependencies among ties and therefore include less plausible network scenarios. In this paper we investigate the use of network models that explicitly incorporate tie dependence. In particular, we consider exponential random graph models, and show how they can be applied to reconstruct networks coherent with Burts arguments on closure and structural holes (Burt 2001). The approach is illustrated on data from the Middle Bronze Age in the Aegean.

Random multigraphs and aggregated triads with fixed degrees

Random multigraphs with fixed degrees are obtained by the configuration model or by so called random stub matching. New combinatorial results are given for the global probability distribution of ed ...