One of the most common measures used in network analysis is betweenness centrality. In this article, you will learn how to make use of it and which algorithms are used to calculate it.

For decades, archaeologists have been trying to create meaningful engagement with stakeholder communities. The continued development of the internet has provided new and diverse opportunities for participation, but also a variety of new hurdles.

In order to get a good understanding of the inner workings of network analysis, you need to get familiar with the mathematical algorithms that are used to generate the networks.

One of Josho’s favourite episodes of the science-fiction television series Star Trek: Voyager (1995-2001) deals with the problems inherent in reconstructing the past, how the past influences the present, and how it paves the way to the future.

Continuing her series on network analysis, Arianna explains how graphs are not only tools to use in your research, but also powerful instruments to show your results to others. She explains how you can manipulate your graphs to present information.

In network analysis, the shape of the network that you build, as well as what your graph looks like, and in general the results of the analysis, all depend on the matrix. Therefore, the way you structure the matrix is important.

In this second article in a series on the chronology of Early Iron Age Greece, Matthew looks at the different ways in which archaeologists and historians ascribe absolute or calendar dates to the relative chronology discussed in Part I.

In this article, the fourth in a series on network analysis, Arianna reviews three software applications that she has tried for her research. She will explain the reasons why she opted to use ORA.

Our understanding of the ancient world depends on its chronology – the order in which events happened and the time elapsed in between them. In this series of articles, Matthew will look at how the chronology of the Early Iron Age or “Dark Age” of Greece has been constructed, and new radiocarbon dates that suggest a radical revision of that chronology.

When studying networks, there are fundamental aspects that you need to consider and options that you need to weigh during the first steps of your analysis.