In the first part of this blog post, we discussed the first studies in graph theory and social network analysis. Then, we introduced several concepts: random networks, weak ties, two-mode networks, centrality measures, the focus theory, network visualization, and structural holes. Now, let us move on to some applications and yet new concepts!
Last September, as part of our seminar series, “60 minutes of DH”, at the IEG, I presented an introduction to historical (social) network analysis. In the talk, I gave an overview of the field’s history, discussing landmark papers, in my opinion. It was a mix of going through papers fundamental to shaping the discipline (a kind of consensus in the network science/social network analysis communities) and those that are important to me or I like. In the following, I will recount this biased – based on my opinion – talk about the evolution of networks research in this two-part post.
At the beginning of March, I went to New Zealand for a research visit with a planned duration of four weeks. This visit was part of a collaboration involving the IEG DH Lab and Te Pūnaha Matatini, a New Zealand centre of research excellence for complex systems and data science hosted by the University of Auckland’s Department of Physics.
The main goal of the visit was to further develop our research on the structure of higher-order networks, that is, networks which account for interactions between individuals stemming from their membership to groups. Higher-order networks are usually represented by either bipartite (two-mode) networks, or hypergraphs, or simplicial complexes. Our last publications on this topic can be seen in the Journal of Complex Networks and the Physical Review E (also available on arXiv, here and here).
I arrived about one week before New Zealand closed its borders to the world, allowing only citizens and long-term residents to enter into the country. „Research visit in New Zealand: Modelling the spread of COVID-19 on higher-order networks“ weiterlesen