Ancient regional routes were vital for interactions between settlements and deeply influenced the development of past societies and their "complexification". At the same time, since any transportation infrastructure needs some level of inter-settlement cooperation to be established, they can also be regarded as an epiphenomenon of social interactions at the regional scale. Here, we propose to analyze ancient pathway networks to understand the organization of cities and villages located in a certain territory, attempting to clarify whether such organization existed and if so, how it functioned.To address such a question, we chose a quantitative approach. Adopting network science as a general framework, by means of formal models, we try to identify how the collective effort that produced the terrestrial infrastructure was directed and organized. We selected a paradigmatic case study: Iron Age southern Etruria, a very well-studied context, with detailed archaeological information about settlement patterns and an established tradition of studies on terrestrial transportation routes, perfectly suitable for testing new techniques. The results of the modelling suggest that a balanced coordinated decision-making process was shaping the route network in Etruria, a scenario which correlates well with the picture elaborated by different scholars using a more traditional technique.
The period between the beginning of the Early Iron Age and the end of the Archaic Period is a time of changes and developments in the Italian Peninsula, which led to the creation of regional ethnic and political groups and to the formation of the first citystates in Western Europe. In the present study, we focus on the evolution of terrestrial route network in the Tyrrhenian region of Latium vetus as it has been hypothesized by scholars from the archeological evidence. Our main goal is to investigate the mechanisms linking decision making processes and the structure of transportation networks. We first attempted to replicate some of its features applying three models previously elaborated for the neighboring region of Southern Etruria. Since it was not possible to attain entirely satisfactory results, we modified the model that performed better in the Etruscan region by including a tunable amount of rich-get-richer bias, which improved considerably its performance. Our results suggest that coordinated decision making with a slightly unbalanced power was responsible for the peculiar characteristics of the route network topology of Latium vetus. Moreover, the mechanism implemented by this model implies that places located at favorable positions can build on their initial advantage and get more and more powerful. This fits very well with the picture elaborated by different scholars on the nature of power balance and dynamics in this region.
The objective of this work is to better analyse and understand social self-organization in the context of social media and political activism. More specifically, we centre our analysis in the presence of fractal scaling in the form of 1/f noise in different Twitter communication networks related to the Spanish 15M movement. We show how quantitative indexes of brown, white and pink noise correlate with qualitatively different forms of social coordination of protests: rigidly organized protests (brown noise), reactive-spontaneous protests (white noise) and complex genuinely self-organized protests (pink noise). In addition, pink noise processes present correlations that reach much further in time, maintaining a dynamical coherence that last several days, and also show a balance between mean distance and clustering coefficient within the interaction network.
Nowadays, it is a common knowledge that scholars from different disciplines, regardless of the specificities of their research domains, can find in network science a valuable ally when tackling complexity. However, there are many difficulties that may arise, starting from the process of mapping a system onto a network which is not by any means a trivial step. This article deals with those issues inherent to the specific challenge of building a network from archeological data, focusing in particular on networks of archeological contexts. More specifically, we address technical difficulties faced when constructing networks of contexts or sites where past interactions are inferred based on some kind of similarity between the corresponding assemblages (Archeological Similarity Networks or ASN). We propose a basic characterization in formal terms of ASN as a well-defined class of networks with its own specific features. Throughout the article, we devote special attention to the problem of quantifying the similarity between sites, especially in relation with the ubiquitous issues of data incompleteness and the reliability of the inferred ties. We argue that, generally speaking, human past studies are quite disconnected from the rest of interdisciplinary applications of network science and that this prevent this field from fully exploiting the potential of such methods. Our goal is to give hints about which are the interesting questions that archeological applications put on the table of network scientists. We suggest that such questions need to be translated into formal terms in order to be properly addressed within the framework of interdisciplinary collaborations. At this aim, a computational experiment is devised as an illustrative example of how simple models can help the cause.
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