How do social networks evolve over huge time-scales? How did geography constrain or enhance the development of past social networks? Can networks of objects tell us about the cultures that make them? Can we use networks of links on Wikipedia to study collective memory?
The TORCH PastNet network will explore answers to these questions at our day-long hackathon on 11 May, by looking at how networks can be used to study the past — pre-history, history, or simply our collective memory. We welcome participants from all disciplines, including the humanities and both social and computational sciences.
In the morning we will have four expert-led workshops, where specific approaches to network studies of the past will be taught, followed by lunch and the proper hackathon event. During lunch, participants will split into interdisciplinary teams and decide upon which directions to follow and which research question to answer. Datasets and questions will be provided, but you are more than welcome to bring your own too!
At the end of the day each group will present their findings; the team with the most interesting and creative analysis will be awarded prizes. Successful teams will also have the opportunity to develop their hackathon projects into further research, being invited to submit proposals after the hackathon to win £300-600 in research funding.
We welcome participants from any and all backgrounds. If you have no programming skills and/or have not analysed network before, or if you have never no background in history, archaeology, or any social science, don’t worry—there will be plenty of opportunities for you to contribute, and experts on all fields will be on hand to help.
If you have any questions please email us at email@example.com. There is limited space so we recommend that you RSVP as early as possible!
10.00-10.30: Introduction and overview of the day
10.30-12.30: Workshops led by Tom Brughmans (network science in archaeology), Martin Poulter (Wikidata and museum collections), and Patrick Gildersleve (Wikipedia and networks of navigation)
12.30-13.30: Team formation and working lunch
13.30-17.00: Data analysis (tea and coffee provided)
17.00-18.00: Presentation of findings and prizes for the winning teams